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Content uploaded by Kalim Gonzales
Author content
All content in this area was uploaded by Kalim Gonzales on Dec 10, 2018
Content may be subject to copyright.
HOW BILINGUALS PERCEIVE SPEECH
2
Abstract
Bilinguals understand when the communication context calls for speaking a particular
language and can switch from speaking one language to speaking the other based on such
conceptual knowledge. There is disagreement regarding whether conceptually-based
language selection is also possible in the listening modality. For example, can bilingual
listeners perceptually adjust to changes in pronunciation across languages based on their
conceptual understanding of which language they’re currently hearing? We asked French-
and Spanish-English bilinguals to identify nonsense monosyllables as beginning with or
, speech categories that French and Spanish speakers pronounce differently than English
speakers. We conceptually cued each bilingual group to one of their two languages or the
other by explicitly instructing them that the speech items were word onsets in that language,
uttered by a native speaker thereof. Both groups adjusted their – identification boundary
as a function of this conceptual cue to the language context. These results support a bilingual
model permitting conceptually-based language selection on both the speaking and listening
end of a communicative exchange.
Keywords: language switching, speech perception, top-down processing, neural
network models, rational listener
HOW BILINGUALS PERCEIVE SPEECH
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1. Introduction
A fundamental challenge of communicating in more than one language is that the
speech signal often calls for different interpretations depending on which language is being
spoken. For example, the English word sea () comprises two speech categories ( and
) that not only occur in the same order, but are each pronounced very similarly in the
Spanish word sí (; “yes”). In other words, these English and Spanish lexical items are
nearly the same in form despite meaning very different things. For a Spanish-English
bilingual, then, hearing each word may trigger unwanted activation of the other word’s
meaning. In this descriptive analysis, of course, the two languages share incongruent overlap
only at the lexical level. At the sublexical level, they are wholly congruent, inasmuch as the
beginning of each word corresponds phonetically to an in both languages and the end of
each word to an in both. It is not the case, for example, that the beginning of sea
corresponds to an in English but to an in Spanish. However, languages do additionally
exhibit such sublexical-level incongruence. For example, Spanish actually corresponds
phonetically to English , as discussed in more depth below. When units of speech overlap
incongruently across languages, how might bilingual listeners avoid confusing them?
1.1. Conceptual cueing hypothesis
Much previous research has focused on the idea that bilingual listeners disambiguate
cross-language overlap by exploiting other aspects of their perceptual input cueing which
language is being spoken (e.g., Carlson, 2018; Grosjean, 1988; Hazan & Boulakia, 1993; Ju
& Luce, 2004; Lagrou, Hartsuiker, & Duyck, 2013; Molnar, Ibáñez-Molina, & Carreiras,
2015; Quam & Creel, 2017; Schulpen, Dijkstra, Herbert, Schriefers, & Hasper, 2003; Singh,
HOW BILINGUALS PERCEIVE SPEECH
4
Poh, & Fu, 2016; Singh & Quam, 2016). Such other aspects potentially include any
perceptual patterns associated more strongly with the target language than with the other
language in long-term memory. Examples range from linguistic aspects like language-
specific vowels and consonants (e.g., the in Spanish frío; Gonzales & Lotto, 2013), to
nonlinguistic aspects like the identifying facial and vocal features of an acquaintance who
speaks only the target language (Molnar et al., 2015). Expanding this focus, the present study
tested the hypothesis that bilingual listeners might go beyond their perceptual input to exploit
their own conceptual understanding of which language is actually being spoken. It is already
well established that bilinguals can use such conceptual knowledge of the communication
context at least to produce, as opposed to perceive, the target language (e.g., Grosjean, 2008;
Tare & Gelman, 2010). Thus, a Spanish-English bilingual addressing a stranger in English
might readily switch to speaking Spanish upon being informed by a third party that the
stranger knows only the latter language. This type of language switching cannot be attributed
to a mere association in long-term memory between the unfamiliar person’s identifying
features and the target language. Rather, it implicates conceptual knowledge of the language
context. Under the hypothesis investigated here, bilinguals might use such knowledge not
only to produce the relevant language when they themselves are speaking, but also to
perceive that language when the other person begins to speak. For example, a bilingual might
use his or her conceptual knowledge that the interlocutor knows only Spanish to avoid
mistaking that speaker’s Spanish sí for English sea, or Spanish for English .
1.2. Mixed support from bilingual models
Conceptually-cued language selection in the listening modality would imply that
HOW BILINGUALS PERCEIVE SPEECH
5
bilinguals’ interpretation of the speech signal is modulated by abstract representations of their
two languages (e.g., “I’m hearing Language X”). This accords with a few prominent models
of bilingual language processing (Dijkstra & Van Heuven, 2002; Green, 1998; Grosjean,
2008). Léwy and Grosjean’s BIMOLA (Bilingual Model of Lexical Access) implements the
theory that bilinguals can operate in different “monolingual modes” (Grosjean, 1988;
Grosjean, 2008). Specifically, bilinguals may choose one language (typically unconsciously)
as the most active and thus most influential on processing, while simultaneously minimizing
activation of the other language. Inspired by TRACE (McClelland & Elman, 1986),
BIMOLA has three ascending layers of nodes, one each for feature, phoneme, and word
units. Of these layers, only the feature layer is shared between languages; the phoneme and
word layers are language-specific. A monolingual mode is simulated by pre-activating the
target language’s word and phoneme sublayers. The underlying assumption is that these
sublayers can be selectively activated by external sources pertaining to language mode,
including conceptual knowledge of which language the interlocutor is speaking. Another
model that permits conceptually-cued language selection is Green’s (1998) Inhibitory Control
(IC) model, derived from a model of action by Norman and Shallice (1986). The IC model
posits that bilinguals construct mental schemas that allow them to perform various
communicative “actions”, including producing and comprehending speech. Separate schemas
are constructed for the two languages. These schemas then compete to control the output of a
lexico-semantic system wherein linguistic representations are tagged for language
membership. The two schemas can be differentially activated by a supervisory attentional
system that monitors language processing with respect to the bilingual’s communicative
HOW BILINGUALS PERCEIVE SPEECH
6
goals, like using a particular language in accordance with conceptual knowledge about the
current language context. Finally, Dijkstra and Van Heuven’s (2002) BIA+ model likewise
assumes that bilinguals construct language schemas sensitive to conceptual knowledge about
the language context. In the BIA+, however, these schemas do not change the activation
levels of the two languages, consistent with the view that both languages always get
activated. Instead, the schemas use decision criteria to select between the two jointly
activated languages.
Research to date does not, however, rule out a model of listeners’ language selection
capacity that is simpler than any of the above—a model without any mechanisms for
harnessing conceptual knowledge about the language context (e.g., language tags and
language schemas). An example would be Macnamara’s classic two-switch model
(Macnamara, 1967; Macnamara & Kushnir, 1971). This model assumes that high-level
cognitive states, such as a conceptual understanding of the language context, can guide
language selection only in an output modality like speaking. In an input modality like
listening, language selection is a deterministic function of the perceptual input. Other
examples, which highlight the potential power of strictly perceptually-based language
selection, include more recent models designed to simulate unsupervised bilingual learning
(French, 1998; Li & Farkas, 2002; Shook & Marian, 2013). When these models are trained
on a corpus of bilingual input, they divide elements from the two languages into separate
clusters. They do so by exploiting the tendency for elements within the same language to
occur closer in time. A subset of these “self-organizing” models additionally exploit the
tendency for same-language elements to share greater phonological similarity (Li & Farkas,
HOW BILINGUALS PERCEIVE SPEECH
7
2002; Shook & Marian, 2013). Once the two language clusters emerge, a language-specific
input pattern (e.g., Spanish vs. English ) will activate any existing representation of
that pattern within the corresponding language cluster. Activation will then spread to other,
interconnected, representations within the same cluster (Shook & Marian, 2013). In theory,
this type of perceptual “priming” of a particular language can aid in subsequently mapping to
that language other of its constituent patterns whose language membership is more
ambiguous (e.g., Spanish rather than English ). In Shook and Marian’s (2013)
BLINCS model, each language cluster incorporates not only phonemes and words but also
various other perceptual patterns co-occurring with these elements, including visible
articulatory gestures and orthographic characters. On a miniature scale, this elaborate self-
organizing network captures the general idea that each language comes to be internalized as a
rich multimodal constellation of linguistic and nonlinguistic patterns typifying the context
wherein it is experienced (Hernandez, Li, & MacWhinney, 2005; Kandhadai, Danielson, &
Werker, 2014). In principle, each language can then be primed, and language ambiguous
forms hence disambiguated, by any linguistic or nonlinguistic patterns uniquely represented
in the corresponding language cluster, without the need for conceptual knowledge about the
language context.
1.3. Debating the utility of conceptual cueing to bilingual listeners
Besides by comparing bilingual models, another way to think about whether
bilingual listeners might select between their two languages based on their own conceptual
understanding of which language is being spoken is to consider the extent to which these
listeners might benefit from such an approach. Several arguments have been made that they
HOW BILINGUALS PERCEIVE SPEECH
8
might benefit very little from this approach, but we will argue to the contrary. One
assumption underlying some of these arguments has been that conceptually-based language
selection is cognitively demanding (Caramazza, Yeni-Komshian, & Zurif, 1974; Macnamara
& Kushnir, 1971). Perceptually-based selection, in contrast, may be driven by preattentive
processes, like those recently postulated by Bosker, Reinisch, and Sjerps (2017) to underpin
auditory contrast effects in research outside of the bilingual literature (e.g., Liang, Liu, Lotto,
& Holt, 2012). A second assumption has been that bilingual listeners find little need for
conceptually-based selection (Hartsuiker, Van Assche, Lagrou, & Duyck, 2011; Grainger,
Midgley, & Holcomb, 2010; Vitevitch, 2012). Seeking quantitative support, Vitevitch (2012)
employed corpus analyses to assess the degree of phonological overlap between Spanish and
English word forms. He found that less than 5% of words in each language were similar
enough to any words in the other language to constitute their “phonological neighbors”. Two
words are said to be phonological neighbors if they bear a common phoneme sequence after a
single phoneme in either word is deleted, added, or replaced. An example of phonological
neighbors across English and Spanish would thus be English pan () and Spanish pan
(“bread”;
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mechanism based other than on the perceptual aspects of the input itself. Therefore, the
cognitive costs incurred from developing or using any such mechanism may outweigh the
benefits.
HOW BILINGUALS PERCEIVE SPEECH
9
There is, however, an important limitation of Vitevitch’s (2012) corpus analyses, as
well as of other investigators’ less formal comparisons between languages that likewise
suggest minimal cross-language overlap (Grainger et al., 2010; Hartsuiker et al., 2011). All of
these comparisons focused exclusively on overlap between whole word forms, such as
between English pan and Spanish pan$
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Marian & Spivey, 2003)-# oor!./"auta
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8assumption of many models, both of
monolingual and of bilingual processing (e.g., Dijkstra and Van Heuven, 2002; Grosjean,
2008; McClelland & Elman, 1986; Shook & Marian, 2013), is that accurate recognition of a
word is facilitated by accurate detection of its sublexical elements, including its onset sound.
In the case of Spanish pan, for example, accurate recognition would be facilitated by accurate
HOW BILINGUALS PERCEIVE SPEECH
10
detection of its onset . Recall, however, that Spanish overlaps incongruently with
English , an incongruence that may increase Spanish-English bilinguals’ risk of
mishearing this word as starting with .
Importantly, this incongruent cross-language overlap at the sublexical rather than
lexical level is but one example of such overlap, which arises from a common phenomenon in
which different linguistic systems distinguish the same vowel and consonant categories
differently (e.g., E. S. Levy, 2009; Lisker & Abramson, 1970; Niedzielski, 1999). Regarding
this particular example, languages do not always distinguish voiced from voiceless stops
(e.g., 9–, –, and – the same way along the dimension VOT (Voice Onset Time).
VOT refers to the duration between when a stop is released at the lips and when the vocal
folds begin vibrating (Lisker & Abramson, 1970). By convention, a negative VOT value
denotes the amount of time by which vocal fold vibration precedes (“leads”) the consonantal
release and a positive value the amount of time by which it follows (“lags”). In some
languages, including Spanish and French, voiced stops like are typically distinguished
from voiceless stops like by vibrating the vocal folds long before releasing the consonant
rather than shortly thereafter. That is, voiced stops differ from voiceless stops in that they are
typically long-lead stops with large negative VOT values rather than short-lag stops with
small positive VOT values (Hay, 2005; Hazan & Boulakia, 1993; Kehoe, Lleó, & Rakow,
2004; Kessinger & Blumstein, 1997; Lisker & Abramson, 1970; Macleod & Stoel-Gammon,
2009; Sundara, Polka, & Baum, 2006; Williams, 1977). In some other languages like English
and German, however, voiced stops are actually typically produced like French and Spanish
voiceless stops, as short-lag stops. Voiceless stops are instead typically produced with
HOW BILINGUALS PERCEIVE SPEECH
11
relatively longer voicing lag, as long-lag stops (Hay, 2005; Hazan & Boulakia, 1993; Kehoe
et al., 2004; Kessinger & Blumstein, 1997; Lisker & Abramson , 1970; Macleod & Stoel-
Gammon, 2009; Sundara et al., 2006; Williams, 1977). In short, some languages’ voiceless
stops like overlap on the VOT dimension with other languages’ voiced stops like due
to a difference between languages in how they contrast voiced and voiceless stops on this
dimension.
1.4. Empirical gap
In the present study, we asked whether bilingual listeners are capable of harnessing
their conceptual knowledge of the language context to negotiate a cross-language difference
in how utterance-initial voiced and voiceless stops are pronounced. Dating back to the early
70’s, previous research on bilingual listeners’ ability to negotiate this type of cross-language
difference has been strongly motivated by studies on the relationship between monolinguals’
production and perception (e.g., Caramazza, Yeni-Komshian, Zurif, & Carbone, 1973; Hay,
2005; Kessinger & Blumstein, 1997; Lisker & Abramson, 1970; Macleod & Stoel-Gammon,
2009; Williams, 1977). These motivational studies indicate that when monolingual speakers
of different languages diverge on how they pronounce voiced and voiceless stops, they
correspondingly diverge on how they identify these stops. For example, Hay (2005) recorded
Spanish and English monolinguals’ productions of - and -initial words in these
speakers’ respective languages. She then had each group identify as or tokens from
a synthetic VOT continuum with these two syllables at its endpoints. Not surprisingly, results
from the speaking task showed that Spanish monolinguals’ typically long-lead and short-
lag productions were optimally separable at a lower value on the VOT dimension than
HOW BILINGUALS PERCEIVE SPEECH
12
were English monolinguals’ typically short-lag and long-lag productions (−12 vs.
+33.4 ms, respectively). More interestingly, results from the listening task revealed that
Spanish monolinguals correspondingly shifted from labeling tokens to labeling them
at a lower value on the VOT continuum as compared to English monolinguals (+.86 vs.
+16.63 ms, respectively)—this despite hearing the exact same continuum (see also Lisker &
Abramson, 1970; Williams, 1977). Further evidence for such a VOT production–perception
correspondence in monolinguals comes from comparisons between French and English
monolinguals (Caramazza et al., 1973; Kessinger & Blumstein, 1997; Macleod & Stoel-
Gammon, 2009). This repeated finding from monolinguals has thus raised an interesting
question concerning bilinguals who speak two languages that implement voiced–voiceless
stop contrasts differently: Do these bilinguals adjust their voiced–voiceless identification
boundary according to which language they are currently hearing?
In seminal work by Caramazza and colleagues (Caramazza et al., 1973), French-
English bilinguals completed speaking and listening tasks in both French and English
contexts. The contexts differed in location (French-speaking high school vs. English-speaking
university), the language of task instructions, and the language bilinguals spoke during the
speaking task. The speaking task entailed reading aloud stop-initial words in the context-
relevant language and the listening task identifying, as voiced or voiceless, monosyllabic
tokens spanning synthetic 9–, –, and – VOT continua. With respect to
distinguishing between these voicing contrasts, results indicated that bilinguals performed in
a more Frenchlike manner in the French than English context only on the speaking task. On
the listening task, bilinguals performed the same way in both contexts. More specifically,
HOW BILINGUALS PERCEIVE SPEECH
13
their voicing identification boundary remained fixed across contexts, lying intermediate
between French and English monolinguals’ identification boundaries. Caramazza and
colleagues later replicated this failure on the part of bilinguals to adjust their identification
boundary across language contexts (Caramazza et al., 1974). To explain bilinguals’
performance, the authors invoked Macnamara’s two-switch model (Caramazza et al., 1974).
They reasoned that bilinguals performed exactly as one would expect if language-switching
in the listening modality is indeed stimulus controlled, since bilinguals heard the same
continuum tokens in both contexts.
To this day, this conclusion has not yet been subjected to empirical scrutiny. To be
sure, numerous studies have since found that bilingual listeners actually can adjust their
identification boundary across language contexts (see Simonet, 2016). However, these studies
were designed simply to show that bilingual listeners fare better at switching between
languages when afforded more proximal perceptual cues to the target language. Thus, some
of these studies prepended target-language phrases to continuum tokens and/or interspersed
such phrases with the continuum tokens (Elman, Diehl, & Buchwald, 1977; Flege & Eefting,
1987; García-Sierra, Diehl, & Champlin, 2009; Hazan & Boulakia, 1993). Some of the
studies embedded target-language phonetic cues directly in the continuum tokens (Casillas &
Simonet, 2018; Gonzales & Lotto, 2013; Hazan & Boulakia, 1993; Osborn, 2016; Zampini &
Green, 2001). One study attached target-language orthography to response buttons (Antoniou,
Tyler, & Best, 2012), while another had participants silently read a target-language magazine
while their ERP responses to continuum tokens were being recorded (García-Sierra, Ramirez-
Esparza, Silva-Pereyra, Siard, & Champlin, 2012). Because of such perceptual cues, one
HOW BILINGUALS PERCEIVE SPEECH
14
cannot exclude the possibility that bilinguals’ perception was a deterministic function of these
cues—unaffected by any conceptual knowledge of the language context. That is, none of
these studies manipulated conceptual knowledge of the language context independently of
perceptual cues, as is necessary to determine whether such knowledge can influence bilingual
listeners’ spoken language processing. Notably, the same empirical gap exists in bilingual
research focusing on other aspects of listening, including bilinguals’ processing of
suprasegmental features (Quam & Creel, 2017; Singh et al., 2016; Singh & Quam, 2016),
phonotactic sequences (Carlson, 2018), and whole word forms (e.g., Blanco-Elorrieta &
Pylkkänen 2016; Grosjean, 1988; Ju & Luce, 2004; Lagrou et al., 2013; Marian & Spivey,
2003; Pellikka, Helenius, Mäkelä, & Lehtonen, 2015). It is for this reason that whether such
conceptual knowledge influences any aspect of bilingual listeners’ language selection
whatsoever remains an open question.
Arguably, then, the strongest indication to date that bilingual listeners might use
conceptual knowledge to select between their two languages comes not from research testing
bilinguals but rather from that testing monolinguals. Studies testing monolinguals
demonstrate that high-level cognitive processes can drive perceptual accommodation to
cross-dialect and cross-gender variation (Johnson, Strand & D’Imperio, 1999; Niedzielski,
1999). For example, Johnson and colleagues instructed monolinguals to imagine that a
gender-neutral voice was male or female while identifying words in that voice. Impressively,
listeners identified the words in a manner consistent with perceptually accounting for gender
differences in the phonetic implementation of the vowels distinguishing hood and hud. Still,
languages are arguably much less similar in form than either dialects or male and female
HOW BILINGUALS PERCEIVE SPEECH
15
voices. Conceivably, one may find two languages that diverge on acoustic-phonetic
dimensions to a similar extent as two dialects or two opposite-gender voices. However, only
languages typically diverge at higher levels of linguistic structure (e.g., words and syntax) to
such an extent as to all but guarantee mutual unintelligibility. From a cognitive efficiency
standpoint, listeners may therefore find less need to go beyond the linguistic signal for cues
distinguishing languages.
1.5. The present study
To investigate whether bilingual listeners can develop a language selection system
sensitive to the communication context at a conceptual level, we extended a previous study of
ours testing Spanish-English bilinguals’ identification of pseudoword-onset stops in Spanish
and English language contexts (Gonzales & Lotto, 2013). In that study, we found that
bilinguals adjusted their voicing identification boundary between the pseudoword endpoints
of a bafri–pafri VOT continuum in accordance with the language context. Bilinguals were
cued to each context both conceptually and perceptually. Bilinguals were cued conceptually
by English instructions stating either that the speaker was a native Spanish speaker and the
to-be-identified bafri and pafri pseudowords rare Spanish words, or that she was a native
English speaker and these two pseudowords rare English words. Bilinguals were cued
perceptually by whether continuum tokens ended with a phonetically Spanishlike or
Englishlike -ri (ɾi–ɾior ɹi–ɹi, respectively). The present study differed
critically from this previous study—and indeed from all previous studies investigating
bilingual listeners’ ability to select between languages—in that we cued each language
context only conceptually. In each context, bilinguals received English instructions stating
HOW BILINGUALS PERCEIVE SPEECH
16
that a native speaker of the target language would, on each trial, begin but not finish saying
one of two ostensible rare words in that language (e.g., bafri and pafri). Tokens were drawn
from a VOT continuum ranging from the beginning of one pseudoword to that of the other
(e.g., –). The continuum did not perceptually cue each context like in our previous
study because it was exactly the same in both contexts.
If bilinguals have some bias toward cognitive efficiency that precludes them from
developing a system for perceptually adjusting to their two languages based on conceptual
knowledge of the language context, then bilinguals should not adjust their voicing
identification boundary across our language contexts distinguished solely by the conceptual
content of the task instructions. Only if bilinguals can in fact develop such a system might
they be expected to adjust their boundary across these contexts. Of course, not all bilinguals
whose two languages exhibit incongruent overlap between voiced and voiceless stops may be
capable of developing such a system. Here we sought to establish the generality of our results
across two highly proficient groups of such bilinguals recruitable at our testing sites—
Spanish- and French-English bilinguals.
2. Method
2.1. Participants
2.1.1. Spanish-English bilinguals
Thirty Spanish-English bilinguals were each randomly assigned to either a Spanish
or English language context. Participating for course credit, these bilinguals were
undergraduate students enrolled in an introductory psychology course at the University of
Arizona, in Tucson (USA). The University of Arizona’s principle language of instruction is
HOW BILINGUALS PERCEIVE SPEECH
17
English, and Tucson is a predominantly English-speaking city. Nevertheless, this city has a
relatively large Spanish-speaking community (Beaudrie, 2011). Participants completed a
questionnaire in which they rated their own proficiency in each language using separate 1–5
scales of how well they spoke and comprehended the language (with 1 denoting “very
poorly” and 5 “almost perfectly”). They then indicated how early they began learning each
language and from whom. Participants were included in the Spanish-English group according
to the same three inclusion criteria as in our previous work (Gonzales & Lotto, 2013). One
criterion was that the participant’s average self-rating in each language was at least 3.5 across
the speaking and comprehension scales (MSpa = 4.5; MEng = 4.75). Another was that any
experience that the participant reported of learning a language other than Spanish and English
was limited to one year or less of formal classroom instruction. The final criterion was that
the participant reported receiving regular exposure to both Spanish and English from one or
more native speakers before age 8 (Mage = 2.33 yrs). This age-of-acquisition cut-off was based
on studies showing distinct neural and behavioral outcomes between second-language
learners divided at or around this cut-off (see Silverberg & Samuel, 2004).
2.1.2. French-English bilinguals
Thirty French-English bilinguals were each randomly assigned to either a French or
English language context.1 These participants consisted of undergraduate students at
Concordia University, in Montreal (Canada). Montreal is located in Quebec, a Canadian
province whose official language is French. However, the city has a large population of
French-English bilinguals (Boberg, 2012) and Concordia’s courses are principally conducted
: One additional participant who met our French-English bilingual criteria was nevertheless excluded for
responding uniformly across all trials, precluding calculation of a voicing identification boundary.
HOW BILINGUALS PERCEIVE SPEECH
18
in English. Due to time limitations, participants at this testing site completed a briefer
questionnaire than those at the University of Arizona—namely, a modified version of the
LEAP-Q (Language Experience and Proficiency Questionnaire; Marian, Blumenfeld &
Kaushanskya, 2007). Participants were included in the French-English bilingual group if they
reported that they began learning both languages before age 8 (Mage = 3.88 yrs), and their
average self-rating in each language was at least 7 across separate 0–10 scales of speaking
and understanding (where 0 denotes “none” and 10 “perfect”; MEng = 9.75; MFre = 8.77).
Unlike our inclusion criteria for Spanish-English bilinguals in Tucson, no restrictions were
placed on experience learning a third language other than that the language was indeed
learned as such (i.e., after French and English). This was to accommodate Montreal’s much
larger proportion of participants proficient in a third language. Additionally, no restrictions
were set regarding how often or from whom participants received early exposure to French
and English, since the LEAP-Q does not directly inquire into these details. However, all but
four bilinguals indicated growing up in a Canadian city where both languages are spoken, and
the four who did not still reported attaining fluency in both languages before age 8. In
summary, then, one can say that our Spanish- and French-English bilingual participants were
all highly proficient in their two languages and likely all received regular exposure to both of
them before age 8.
2.2. Stimuli
2.2.1. Instructions
For both bilingual groups, the instructions that conceptually cued the target language
differed across contexts in two ways. First, these instructions differed in whether they
HOW BILINGUALS PERCEIVE SPEECH
19
introduced the identification-task speaker as a native speaker of English or of the group’s
other language (Spanish or French). Second, they differed in whether they introduced the
pseudowords, which they stated that this speaker would begin but not finish saying aloud, as
rare words in English or in the other language. Thus, for example, Spanish-English bilinguals
in the English context were told that the speaker was a native English speaker and the
pseudowords rare English words. Those in the Spanish context, in contrast, were told that she
was a native Spanish speaker and the pseudowords rare Spanish words. The instructions did
not perceptually cue each context because they were always administered in English,
irrespective of the experimental context.
The instructions were conveyed orally by the experimenter in general terms, and
then via computer in greater detail. The computer-based instructions consisted of pre-
recorded sentences matched word-for-word by on-screen text. As an exception, the
pseudowords, described below, appeared only in the text. This is because these items are the
same across languages only in their orthographic forms. In their spoken forms, the items
differ across languages. This means that in their spoken forms they would have constituted a
reliable perceptual cue to each language context. For the same reason, the experimenter never
pronounced the two items aloud in either language context. For each bilingual group, we first
created the computer-based instructions for the English context. We then transformed a copy
of these instructions for the other language context. We did so simply by replacing every
occurrence of the word English (e.g., …a native English speaker will begin to say…) with
the English word for the group’s other language (e.g., …a native Spanish speaker will begin
to say…). We adopted this procedure to transform both the pre-recorded English sentences
HOW BILINGUALS PERCEIVE SPEECH
20
and the accompanying English text.
2.2.2. Pseudoword stimuli
Spanish/English contexts – The ostensible words for Spanish-English bilinguals
were adopted from our previous work (Gonzales & Lotto, 2013). Spelled bafri and pafri in
both language contexts, these pseudowords were devised to satisfy a number of constraints.
One constraint was that the pseudowords could be spelled the same way in the Spanish
context as in the English context per the two languages’ phoneme-to-grapheme conversion
rules. A second was that neither pseudoword would, in its spoken form, be easily mistaken for
a real word or co-articulated sequence thereof in either language. A third was that, in each
context, the only phonological difference between the two pseudowords was in whether they
began with a voiced or voiceless stop. A fourth was that the orthographic forms of the two
pseudowords could be phonetically implemented as the endpoints both of a Spanish-sounding
VOT continuum and of an English-sounding variant of that continuum differing only in the
pronunciation of the tokens at (or near) their offset. Thus, bafri and pafri were implemented
as the endpoints both of a Spanish-sounding bafri–pafri continuum and of an English-
sounding variant differing only in the pronunciation of tokens’ -ri ending (Spanish-sounding
(ɾi–ɾi) vs. English-sounding ɹi–ɹi).2 Finally, the pseudowords needed to
share an internal fricative or other segment onto which the Spanish and English
pronunciations of the language-specific ending could be interchangeably spliced to create the
) Spanish and English pronunciations of these co-articulated segments are saliently language-specific
primarily because the Spanish rhotic is a tap (/ɾi/) whereas the English rhotic is an approximant (/ɹi/). The
Spanish /ɾ/ is thus phonetically more similar to the English flap, though English speakers do not closely
associate it with any English consonant (Rose, 2012). Similarly, the English /ɹ/ is perceived as foreign-sounding
to Spanish speakers (Dalbor, 1980).
HOW BILINGUALS PERCEIVE SPEECH
21
two versions of the continuum. Thus, bafri and pafri share an internal -f- segment preceding
their shared -ri ending.
For the main task of the present study, in which Spanish-English bilinguals indicated
whether the speaker was beginning to say bafri or pafri, we created a single –
continuum to present in both language contexts to which these participants were assigned.
Earlier we alluded to why we created a single continuum for both contexts. This was so that
any shift in bilinguals’ identification boundary across contexts could not, like their shift in
our previous study, be attributed to the tokens changing in form across contexts to
phonetically match, and thus perceptually cue, each context. An alternative approach to
creating a single relatively language-neutral continuum for both contexts would have been to
likewise create a single continuum for both contexts, only one varying between two whole
pseudowords not sharing any saliently language-specific segments (e.g., bafa and pafa).
However, the present stimuli were designed to be broadly useful for a larger program of
research, including studies probing for a perceptual cueing effect by using whole pseudoword
tokens sharing a language-specific ending.
The –continuum comprised 14 tokens across which only the initial stop
consonant’s VOT value varied, starting at −35 ms and increasing in equal 5 ms steps to +30
ms. Using Praat (Boersma & Weenink, 2010), these tokens were created from natural speech
recorded by an early Spanish-English bilingual. One clearly pronounced Spanish pafri token
() was stripped both of its final three segments, -fri, and of the voiceless interval of its
initial segment, p-, not including the release burst. This Spanish pa- token was designated the
continuum’s 0 ms VOT token. It was transformed into 7 voicing lead tokens ranging in VOT
HOW BILINGUALS PERCEIVE SPEECH
22
from −35 ms to −5 ms. It was also transformed into 6 voicing lag tokens ranging in VOT
from +5 ms to +30 ms. The lead tokens were created by adding to the beginning of the
stripped token (before its release burst) successive prevoicing intervals excised from multiple
different tokens of Spanish bafri (). The lag tokens were created by inserting between
the stripped token’s release burst and its voicing onset successive voiceless intervals from
multiple different tokens of Spanish pafri. All prevoicing and voiceless intervals were
approximately 5 ms long. Some had been slightly trimmed down to this duration via hand
editing, with care taken not to introduce any perceptible clicks into the stimulus. The
resulting – continuum sounded relatively language neutral, with the bilabial stop’s
VOT range falling within both Spanish and English – ranges (Hay, 2005; Lisker &
Abramson, 1970; Williams, 1977) and the following Spanish segment having an English
phonetic counterpart in English ;. Spanish and English ; differ in backness (being
central and back vowels, respectively) but nevertheless overlap in F1–F2 space. Moreover,
these vowels are rated as perceptually very similar by Spanish-English bilinguals (Flege,
Munro, & Fox, 1994).
French/English contexts – The pseudoword stimuli for French-English bilinguals
were devised to satisfy the same five constraints as those for Spanish-English bilinguals,
except with respect to French-English bilinguals’ own two languages. This meant that
French-English bilinguals did not receive a minimal pair whose spellings in both contexts
were, as for Spanish-English bilinguals, bafri and pafri. For our multi-study investigation,
one issue with using these same pseudowords for French-English bilinguals was that the
French pronunciation of pafri would have potentially violated the constraint that no variant
HOW BILINGUALS PERCEIVE SPEECH
23
should be easily mistaken for a co-articulated sequence of real words. The reason is that this
variant might have been easily mistaken for French pas frit (“not fried”), though this was not
an issue specifically in the present study where bilinguals heard only “truncated” pseudoword
tokens. The pseudowords that we devised to satisfy all five constraints were, in both contexts,
instead spelled befru and pefru. In their spoken forms, their shared language-specific ending
is -ru,3 which was not present in the truncated tokens. For both contexts, we created a single
continuum of such tokens ranging from < to <. This continuum was created
analogously to that for Spanish-English bilinguals, thus comprising 14 tokens across which
only the VOT value of the onset stop varied (in equal 5 ms steps from −35 ms to +30 ms).
Tokens were derived from an early French-English bilingual’s French befru and pefru
productions. The resulting continuum sounded relatively language neutral, with the onset stop
spanning a VOT range falling within both French and English – ranges (Caramazza et
al., 1973), and the following French < and segments having English phonetic
counterparts in English < and .
2.3. Procedure
=French and English pronunciations of this -ru ending differ markedly due to both the consonant and the
vowel. French ‘r’ (/ʁ/) is a voiced dorsal fricative described as a novel sound for naïve English listeners. It is
distinct from English ‘r’ (/ɹ/), which is an alveolar approximate, but also from English voiced fricatives, none of
which are dorsal (Colantoni & Steele, 2008). English ‘r’ likewise lacks a perceptual equivalent in French, with
French listeners perceiving it as somewhat /w/-like (Hallé, Best, & Levitt, 1999). French and English
pronunciations of the -ru ending also differ with respect to the vowel segment, though the French vowel (/y/)
may cue French more than the English vowel (/u/) English. French /y/, which combines lip rounding with a
forward tongue body, is said to be a novel sound for naïve English listeners (Flege & Hillenbrand, 1984; Flege,
1987). English has rounded vowel categories, but none defined by tongue-fronting (E. S. Levy, 2009). English-
French bilinguals perceive French /y/ as closest to English /u/ when palatalized (/ju/, as in beauty) but
nevertheless as quite foreign to English (E. S. Levy, 2009). English /u/, on the other hand, may pass perceptually
as French. Although it is quite distinct from French /y/, it has a phonetic counterpart in French /u/ (Flege &
Hillenbrand, 1984; Flege, 1987).
HOW BILINGUALS PERCEIVE SPEECH
24
All participants provided informed consent to participate in the experiment. After
completing our language background questionnaire, they received the general instructions
from the experimenter. They were then seated individually facing a computer monitor, where
they received the computer-based instructions before proceeding to perform the identification
task. Each identification trial began with the appearance of a centrally located black cross,
which participants were instructed to fixate. Approximately 710 ms later, this cross was
automatically replaced by the two pseudowords on either side of the screen, with Spanish-
English bilinguals being visually presented bafri and pafri and French-English bilinguals,
befru and pefru. The side order of the two pseudowords was randomized across participants.
The pseudowords stayed on the screen for the remainder of the trial. Approximately 710 ms
after their onset, a continuum token was delivered via headphones at a comfortable listening
level (Spanish-English bilinguals), or via loudspeakers at an intensity of 70 dB SPL (French-
English bilinguals). Participants were instructed to use the left or right shift key to indicate
whether the speaker was beginning to say the left or right “rare word”, respectively. The trial
terminated on the participant’s key press, or else automatically after 4.1 s elapsed. The 14
continuum tokens were presented in 3 random orders for a total of 42 trials. The computer-
based instructions and identification task were both controlled by DMDX software (Forster &
Forster, 2003).
3. Results
The monolingual speech production studies reviewed early indicate that Spanish,
French, and English all contain contrasting and stops that are separable on the VOT
dimension. However, these studies also indicate that both the Spanish variants of these
HOW BILINGUALS PERCEIVE SPEECH
25
contrasting stops and the French variants are optimally separable at a comparatively lower
VOT boundary value than are the English variants (e.g., Hay, 2005; Kehoe et al., 2004;
Lisker & Abramson , 1970; Macleod & Stoel-Gammon, 2009; Sundara et al., 2006; Williams,
1977). A clear prediction thus follows from the hypothesis that bilingual listeners can develop
a system for selecting between their respective languages based on conceptual knowledge of
the language context. The highly proficient Spanish- and French-English bilinguals tested
here should place their pseudoword identification boundary at a lower VOT value when told
they are hearing their Romance language (Spanish or French) compared to when told they are
hearing English.
3.1. Probability functions
Using logistic regression (see Morrison, 2007), we fitted each participant’s
identification responses to a binary logistic regression model. The model was then used to
predict, at each step along the VOT continuum, the probability of the participant responding
that the speaker began saying the ostensible - rather than -initial word. Fig. 1 shows
each bilingual group’s probability of a -initial response as a joint function of the language
context and continuum token’s VOT value. Within each group and context, we plot median
rather than average probabilities because probabilities at multiple VOT steps are non-
normally distributed across individuals (p < .05 to < .01; Anderson-Darling tests).
HOW BILINGUALS PERCEIVE SPEECH
26
Figure 1. Spanish- and French-English bilinguals’ response probability functions, derived
from logistic regression. The left panel displays Spanish-English bilinguals’ median
probability of responding that they heard the beginning of the ostensible word pafri (rather
than bafri), plotted as a function of the language context and – continuum. The right
panel displays French-English bilinguals’ median probability of responding that they heard
the beginning of the ostensible word pefru (rather than befru), plotted as a function of the
language context and <–< continuum (all error bars denote SEM).
3.2. VOT boundary values
Each participant’s voicing identification boundary was computed using the logistic
regression model fitted to his or her data. Specifically, the model’s intercept and slope
coefficients were used to compute the VOT value where the participant’s & and &initial
responses were equally probable. Fig. 2 displays each bilingual group’s individual boundary
values within the two language contexts. Consistent with our hypothesis, Spanish-English
HOW BILINGUALS PERCEIVE SPEECH
27
bilinguals adopted a lower median boundary value in the Spanish context (+.97 ms, SD =
6.25) than in the English context (+7.94 ms, SD = 60.13). Also consistent with our
hypothesis, French-English bilinguals adopted a lower median boundary value in the French
context (−11.34 ms, SD = 12.5) than in the English context (+5.94 ms, SD = 42.08).
However, neither bilingual group’s cross-context boundary difference was amenable to a
regular two-sample (Student’s) t-test. For each group, this test requires assuming that
individual boundary values are normally distributed within both language contexts and that
the two distributions do not differ from one another in variance. As Fig. 2 shows, each
bilingual group’s data contain three outliers. The three outliers in the Spanish-English
bilingual group’s data are present in the distribution of English boundary values. The outliers
cause this distribution to be skewed significantly rightward (p < .01; skewness test4) and to
hence deviate significantly from normality (p < .01; Anderson-Darling test). They also cause
it to differ significantly in variance from the distribution of Spanish boundary values (p < .05;
Levene’s test). Turning to the French-English bilinguals’ data, the three outliers in these data
are likewise present in the distribution of English boundary values, causing this distribution
to deviate significantly from normality (p < .01). Note, though, that this distribution is not
significantly skewed (p > .90) and does not differ significantly in variance from the
distribution of French boundary values (p > .20).
> We used the Z-test approach (see, e.g., Corder and Foreman, 2009).
HOW BILINGUALS PERCEIVE SPEECH
28
Figure 2. Each bilingual group’s VOT boundary values within the two language contexts,
derived from logistic regression. Individual boundary values are represented by the gray
circles and context medians by the black circles (error bars denote SEM). Each participant’s
individual boundary value is the predicted point on the VOT dimension where he or she
becomes as likely to make a /p/- as a /b/-initial response. Some boundary values fall outside
the continuum tokens’ VOT range (i.e., −35 to +30 ms). They were not computationally
constrained to fall within this range for lack of any a priori basis for such a constraint on the
boundary values of individual listeners.
3.3. WMW test and rank-transformation
A widespread approach to analyzing data unfit for the two-sample Student’s t-test is
to perform the Wilcoxon-Mann-Whitney (WMW) test. When used to compare unpaired
samples, the WMW test is indeed said to be the former test’s nonparametric counterpart. The
HOW BILINGUALS PERCEIVE SPEECH
29
reason is that it analyzes the ranks of observations rather than the raw values themselves
(Zimmerman, 2011). More specifically, each raw observation in the combined sample is
ranked according to its magnitude relative to all the other observations, so as to determine
whether the ranks in one sample are systematically higher or lower than those in the other.
The fact that the WMW test invariably transforms each sample into a set of ranks with a
rectangular-shaped distribution means that it makes no assumption about whether either
sample comes from a normal parent distribution. Further, rank-based variance estimates are
less sensitive to outliers (Fagerland & Sandvik, 2009; Hettmansperger & McKean, 1978),
which can create skewness and variance heterogeneity, as our raw data described above
illustrate. Nevertheless, the WMW test is sensitive to these properties whenever they are
retained in, or even created by, the rank transformation (Fagerland & Sandvik, 2009;
Zimmerman & Zumbo, 1993). Therefore, this test is a suitable nonparametric alternative only
insofar as these properties are absent from the rank transformation. Fig. 3 displays each
bilingual groups’ data after being rank-transformed as when deriving the WMW test statistic
(Conover & Iman, 1985). Specifically, each group’s individual boundary values across the
two language contexts were pooled to form a single series of values (nEnglish + nRomance = 30)
sorted in numerically ascending order. Each boundary value in this series was then replaced
by its ordinal position number, or “boundary rank”. Thus, the lowest of the 30 boundary
values was replaced by a boundary rank of 1, the second lowest by a boundary rank of 2, and
so on up to the highest value, replaced by a boundary rank of 30. Tied values were each
replaced by their average position number. As Fig. 3 shows, neither bilingual group’s rank-
transformed data exhibit significant variance heterogeneity across the two language contexts
HOW BILINGUALS PERCEIVE SPEECH
30
(p > .30 to p > .60) or skewness within either context (p > .10 to p > .90). The WMW test is
thus a suitable nonparametric alternative for both groups’ data.5
Figure 3. Each bilingual group’s boundary ranks within the two language contexts. Gray
circles represent individual boundary ranks and black circles context medians (error bars
denote SEM). Each participant's individual boundary rank represents the magnitude of his or
her boundary value relative to the boundary values of all other participants in the same
bilingual group across both contexts. Thus, the lowest boundary rank represents the lowest
boundary value, the second lowest boundary rank the second lowest boundary value, and so
?This reduction in variance heterogeneity and skewness can be understood as follows. When the raw data
are rank-transformed, each sample with values falling extremely far from its mean in either direction no longer
contains such extreme values, as each value ends up falling just one unit (one rank) away from the next farthest
value in the same direction (whether the next farthest is in the same sample or in the group’s other sample). A
similar effect might likewise be obtained by winzorizing, downweighting, or otherwise truncating the data, but
this latter type of approach typically requires making assumptions about what counts as an outlier and what
counts as a suitable replacement value.
HOW BILINGUALS PERCEIVE SPEECH
31
on (equal ranks represent tied values).
3.4. WMW test results
If bilinguals tend to adopt a lower identification boundary in the context cueing their
Romance language than in that cueing English, their mean boundary rank should be
systematically lower in the former context. To test this prediction, we submitted each
bilingual group’s data to a two-tailed WMW test with context as the between-subjects factor
(alpha set at .05). Fig. 3 shows each bilingual group’s mean boundary rank within the two
language contexts. Consistent with our prediction, Spanish-English bilinguals’ cross-context
difference in boundary rank is significant (W = 280.50, p = .0488, r = .36), reflecting a
reliable tendency for these bilinguals’ individual boundary ranks to be lower in the Spanish
context (M = 12.30; SD = 7.94) than in the English context (M = 18.70; SD = 8.69). French-
English bilinguals’ cross-context difference is also significant (W = 290.00, p = .0183, r = .
44). Moreover, these latter participants’ cross-context difference likewise reflects a reliable
tendency for their individual boundary ranks to be lower in the context cueing their Romance
language (M = 11.67; SD = 6.72) than in that cueing English (M = 19.33; SD = 9.15).
Together, then, these results indicate that both bilingual groups tended to adopt a lower
identification boundary in the context cueing their Romance language.6
4. General Discussion
Previous research has showcased bilinguals’ ability to switch from speaking one
language to speaking the other based on their conceptual knowledge of the communication
@ For supplementary analyses, see the Appendix
HOW BILINGUALS PERCEIVE SPEECH
32
context (e.g., Grosjean, 2008; Tare & Gelman, 2010). The present study investigated whether
conceptually-based language selection is also possible in the listening modality. We
conceptually cued French- and Spanish-English bilinguals either to their Romance language
(French or Spanish) or to English. We did so by explicitly instructing bilinguals that they
were going to perform a word identification task wherein a speaker of the language in
question would begin, but not finish, saying one of two rare words in that language. The two
“rare words” were actually pseudowords, contrasting voiced and voiceless onsets
(e.g., bafri and pafri). Identification tokens varied along the VOT dimension from the first
syllable of one pseudoword to that of the other (e.g., –). We predicted that both
bilingual groups would apply different voicing identification criteria depending on which
language they were instructed they were hearing. We made this prediction because these two
bilingual groups’ respective Romance languages both contrast voiced and voiceless stops
differently than English. More specifically, both Spanish and French variants of voiced and
voiceless stops are optimally separable at a lower VOT boundary value compared to English
variants (e.g., Hay, 2005; Kehoe et al., 2004; Lisker & Abramson , 1970; Macleod & Stoel-
Gammon, 2009; Sundara et al., 2006; Williams, 1977). Consequently, Spanish and French
voiceless stops overlap incongruently with English voiced stops on the VOT dimension.
Consistent with both bilingual groups accounting for this incongruent cross-
language overlap, both groups placed their voicing identification boundary at a lower VOT
value when cued to their Romance language than when cued to English. Critically, these
results cannot be explained in terms of bilinguals being perceptually, rather than conceptually,
cued to the target language. Unlike in previous studies, we did not vary any auditory or visual
HOW BILINGUALS PERCEIVE SPEECH
33
stimuli across our conceptually-cued language contexts in order to perceptually match each
context. For example, we did not vary the language of instructions (always in English) or of a
more local linguistic environment surrounding continuum tokens (e.g., carrier phrases) to
match each context. Nor did we perceptually cue each context by varying the phonetic
makeup of the continuum tokens themselves, which were held constant across contexts. Put
simply, all that distinguished the two contexts was the conceptual content of the verbal
instructions, thus implicating this conceptual information in bilinguals’ context-specific
voicing identifications.
4.1. Conceptual knowledge of the target language facilitates language selection for the
listener, too
These results thus provide the first clear evidence favoring a bilingual model of
language selection in which conceptual knowledge about the language context can be
exploited in the listening modality just as in the speaking modality (Dijkstra & Van Heuven,
2002; Green, 1998; Grosjean, 2008). In the language of Green’s IC model, bilingual
participants may have achieved such language selection with the aid of a supervisory
attentional system. Based on our explicit instructions cueing the target language, this system
may have activated a target-language schema biasing perception toward target-language
representations, as of a Spanish-tagged rather than English-tagged when the target
language was Spanish. The system may have then maintained strong activation of this
schema by inhibiting a competing nontarget-language schema, activated automatically (albeit
perhaps minimally) by VOT values equally compatible with both speech categories. As
alluded to above, the two language contexts were not reliably distinguished by any perceptual
HOW BILINGUALS PERCEIVE SPEECH
34
information associated in long-term memory with the target language (e.g., real Spanish vs.
English words, or a familiar Spanish vs. English monolingual). Therefore, one might suppose
further that bilinguals labeled tokens differently across the two contexts because the
supervisory attentional system directed the target-language schema to make do with make-
shift contextual cues maintained in working memory. This might have amounted to bilinguals
continually reminded themselves that the on-screen orthographic forms of the pseudowords
were introduced as Spanish words, or that the speaker was introduced as a native Spanish
speaker.
4.2. Revisiting assumptions motivating strictly perceptually-driven language selection
Our results challenge an alternative type of language-selection model according to
which selection in an input modality is a deterministic function of the perceptual input itself.
It is therefore worth revisiting the assumptions that have motivated such an alternative model.
Recall that one assumption has been that conceptually-based language selection is more
effortful than perceptually-based selection (Caramazza et al., 1974; Macnamara & Kushnir,
1971). We would not dispute this assumption per se. As just suggested, conceptually-based
language selection might recruit “top-down” inhibition and working memory processes,
whereas perceptually-based selection might proceed automatically from “bottom-up” cues.
We would just qualify this assumption by emphasizing that whatever cognitive resources get
expended toward conceptually-based language selection may, on average, get expended
anyway. While only conjectural at this point, this possibility can be understood within the
ideal listener framework. Within this framework, the ideal listener is seen as holding a belief
about the input’s underlying structure. However, his or her belief is seen as comprising
HOW BILINGUALS PERCEIVE SPEECH
35
multiple uncertain estimates (e.g., Kleinschmidt & Jaeger, 2015; Pajak, Fine, Kleinschmidt,
& Jaeger, 2016). The rationale for this uncertainty is that the input is inherently noisy and
ambiguous, with constant variation across social groups, individuals, and speaking styles
(Heald & Nusbaum, 2014). The ideal listener continually updates his or her probabilistic
belief about the underlying structure of the input for the highest likelihood of being accurate.
This updating process entails incrementally integrating prior knowledge with all available
incoming information from the input itself. As Kuperberg and Jaeger (2016) theorize, this
process may very well incur a cost when conceptual knowledge is used to inhibit context-
irrelevant hypotheses. On average, however, it should reduce how much probability gets
assigned to such erroneous hypotheses. This, in turn, should reduce “surprisal”—a theoretical
quantification of how much probability must be redistributed across the hypothesis space to
reflect new evidence favoring the correct hypothesis over erroneous ones (R. Levy, 2008).
Critically, R. Levy and others have shown that surprisal correlates positively with processing
difficulty. Thus, conceptually-based language selection may indeed incur a processing cost,
but one generally counterbalanced by a downstream reduction in surprisal and hence in
processing difficulty. Interestingly, this theoretical framework offers a unifying way of
understanding both the present results and previous results demonstrating monolinguals’ use
of conceptual cues to negotiate within-language phonetic variation (Johnson et al. 1999;
Niedzielski, 1999).
The other assumption has been that strictly perceptually-based language selection is
generally sufficient for selecting the relevant language (Grainger et al., 2010; Hartsuiker et
al., 2011; Vitevitch, 2012). The implication is that even if the processing cost incurred from
HOW BILINGUALS PERCEIVE SPEECH
36
conceptually-based language selection is fully offset by reduced surprisal, listeners may find
little incentive to develop a system supporting such selection in the first place. Vitevitch’s
(2012) work represents the most rigorous effort to date to validate this rich input assumption.
His corpus analyses suggest minimal phonological overlap between English and Spanish
word forms. Nevertheless, these analyses overlook numerous potential sources of language
confusion, accounting only for cross-language overlap between whole word forms, such as
between English pan () and Spanish pan (. Most relevant to the present study,
these analyses do not account for cross-language overlap between utterance onsets, such as
the case investigated here where the same onset stop may correspond to different sublexical
categories depending on which language is being spoken. Cross-language onset overlap may
also lead to confusion between languages at the lexical level. For example, the consonant
clusters at the beginning of English floor and Spanish flauta correspond to the same sequence
of sublexical categories in both languages (followed by ), so neither cluster would be
expected to lead to cross-language interference at the sublexical level. However, one cluster
constitutes the beginning of a Spanish word whereas the other, the beginning of an English
word. Thus, a Spanish-English bilingual hearing either of these two words unfolding in time
may experience momentary cross-language competition between them for recognition. Future
research should investigate whether bilinguals' conceptual knowledge of the language context
helps them additionally mitigate this latter type of onset-based cross-language interference.
In theory, bilingual listeners may manage to avoid cross-language interference from
overlapping onsets by selecting between languages as a deterministic function of perceptual
cues afforded by the broader language context. In practice, however, perceptual cues may not
HOW BILINGUALS PERCEIVE SPEECH
37
always be so reliable. Consider when a Spanish-English bilingual hears Spanish pan at the
beginning of a Spanish sentence, but before hearing this word hears an English sentence. Up
to around the point when the listener hears this Spanish word, perceptual information from
the broader context may not strongly constrain the listener to identify the word’s onset as
Spanish . Indeed, the listener may hear the Spanish word while still harboring strong
residual activation of English elicited from previously processed perceptual cues to English.
Therefore, the listener may actually be more likely to mistake the onset for English . The
listener may even continue to experience strong bottom-up activation of English as the
Spanish sentence proceeds to unfold beyond the first word. This could happen, for example,
if the speaker producing the Spanish sentence has Anglo facial features (Molnar et al., 2015;
Zhang, Morris, Cheng, & Yap, 2013), or has an English accent (Llanos & Francis, 2016).
Regarding accent, someone speaking English-accented Spanish may still pronounce stop
consonants with a native-like VOT production boundary (Knightly, Jun, Oh, & Au, 2003). In
this case, any phonetic characteristics of the English accent cueing the listener to an English
rather than Spanish boundary would be misleading. Conceptual knowledge about which
language is actually being spoken might help resolve any one of these potential sources of
language confusion.
4.3. From perceptual to conceptual information and back? Processing and
developmental considerations
None of this is to argue that bilingual listeners exploit conceptual knowledge to the
complete exclusion of perceptual cues when selecting between languages. Indeed, a wealth of
previous research indicates that bilingual listeners additionally exploit perceptual cues. In
HOW BILINGUALS PERCEIVE SPEECH
38
early work using a gating task, for example, Grosjean (1988) tested French-English
bilinguals’ ability to recognize an English word (e.g., pick) with a largely overlapping French
counterpart (piquer, meaning “to sting”). Results indicated that recognition was aided by the
two words’ fine-grained phonetic differences. In particular, bilinguals isolated the English
word faster when hearing it pronounced in an English- than French-like manner. Importantly,
this pronunciation effect did not extend to English words lacking largely overlapping French
counterparts. Such evidence for perceptually-cued language selection based on word-internal
cues has since been extended using a variety of other methodologies, including a two-
alternative forced-choice (2AFC) task (Hazan & Boulakia, 1993), cross-modal priming
(Schulpen et al., 2003), eye tracking (Ju & Luce, 2004; Quam & Creel, 2017), and even
preferential looking with children (Singh & Quam, 2016). In addition, other research has
shown perceptual cueing from the phonetics of a sentential context, both in an auditory
lexical decision task (Lagrou et al., 2013) and in a 2AFC task (Llanos & Francis, 2016).
Taken together with this literature, the present study therefore supports the possibility that
conceptual and perceptual cues facilitate bilingual listeners’ language selection interactively.
What might such interactive processing look like? In our study, the two language
contexts were distinguished solely by explicit instructions. Typically, however, bilinguals are
not conceptually cued to each language in this way. Instead, they receive other types of cues,
including both lexico-semantic cues (Zhao, Shu, Zhang, Wang, Gong, & Li, 2008) and
perceptual cues (Hirschfeld & Gelman, 1997; Zhao et al., 2008). Regarding perceptual cues,
Hirschfeld and Gelman (1997) found that adults could judge with high accuracy whether they
were hearing English or Portuguese when the speech samples were rendered unintelligible via
HOW BILINGUALS PERCEIVE SPEECH
39
low-pass filtering, which preserved mostly just prosodic cues. In all the studies reviewed in
the preceding paragraph, perceptual cues to the target language may have similarly activated
a conceptual representation of the target language. We therefore suggest that conceptual
knowledge about which language is being spoken might facilitate language selection whether
that knowledge is activated directly by conceptual cues as in our study, or indirectly by other
types of cues like the perceptual cues in these previous studies. This hypothesized language
selection, driven by top-down knowledge that is itself driven by bottom-up cues, is indeed
consistent with models that permit a role of conceptual knowledge in mapping input to the
target language. In Dijkstra and Van Heuven’s (2002) BIA+, for example, abstract
representations of the two languages take the form of “language nodes”. Each language node
is bidirectionally connected to representations of language-matching linguistic forms. For
example, a Spanish node would share bidirectional connections with representations of
Spanish words, which would in turn share such connections with representations of
constituent phonemes like Spanish . Each language node therefore receives activation
originating from language-matching lexical and sublexical forms, and this bottom-up
activation can in principle influence top-down decision criteria for selecting between
languages (e.g., between Spanish and English ).
Of course, our results do not rule out the possibility that when strong perceptual cues
are available as in previous research, bilingual listeners select between languages as a
deterministic function of these cues themselves (e.g., based on “horizontal” excitatory
connections between Spanish and Spanish . To process the input most efficiently, for
example, they might disregard whatever higher-level conceptual knowledge these cues may
HOW BILINGUALS PERCEIVE SPEECH
40
activate. Input-to-language mappings based on such conceptual knowledge might also be
constrained by cognitive limitations. Such limitations might be specific to certain
populations, such as young children (Singh & Quam, 2016) rather than cognitively mature
adults like those tested here. They might also be specific to certain stages of processing, such
as early stages captured by eye tracking (Quam & Creel, 2017) as opposed to later stages
captured by our 2AFC task. In short, the possibility remains that bilingual listeners frequently
select between languages without exploiting conceptual knowledge about the language
context, either during childhood or thereafter. What our results indicate is that however
frequently the early bilingual listeners tested here might have disregarded such conceptual
knowledge during their bilingual lifetime, they did not do so frequently enough to preclude
development of a language selection system sensitive to such knowledge at least some of the
time.
Our results therefore revive longstanding questions about how this type of system
might develop. Existing models consistent with such a system have been criticized for some
time now for being developmentally opaque (French & Jacquet, 2004; Jacquet & French,
2002; Li, 1998). This is because these models comprise a hardwired network wherein abstract
representations of the two languages take the form of pre-specified language nodes or
language tags (Dijkstra & Van Heuven, 2002; Green, 1998). Alternatively, the form they take
is altogether unaddressed (Grosjean, 2008). This contrasts sharply with the self-organizing
models discussed in the Introduction that exhibit only perceptually-cued language selection
(French, 1998; Li & Farkas, 2002; Shook & Marian, 2013). In these models, the formation of
language clusters proceeds in a principled way from the network’s sensitivity to temporal and
HOW BILINGUALS PERCEIVE SPEECH
41
perceptual input dimensions distinguishing the two languages. One possibility is that
bilinguals begin by forming language clusters much like in these self-organizing models.
Eventually, however, they abstract from the two clusters higher-level representations
supporting conceptually-based language selection (Byers-Heinlein, 2014; Dijkstra & Van
Heuven, 1998; Li & Farkas, 2002; Miikkulainen, 1993). Interestingly, bilinguals who acquire
both languages from early infancy, like many of our participants did, might begin developing
such higher-level representations when they are still preverbal infants. By the end of their
first year, infants can segregate two artificial languages along temporal and perception
dimensions to form abstract representations of language-specific rules (Gonzales, Gerken, &
Gómez, 2015; 2018). Equally telling are results from Liberman, Woodward, and Kinzler
(2016). These authors found that 9-month-olds can already infer that two people are less
likely to affiliate with one another if the two speak different languages. These independent
lines of research thus converge to suggest that infants may begin representing language
variation at some abstract conceptual level before even speaking.
It is worth noting, however, that language clusters may not unilaterally promote
bilingual language development. In a positive feedback loop, language clusters may foster the
development of conceptual representations that then reciprocally foster the development of
these language clusters themselves (see also Grainger et al., 2010). Consider a French-
English bilingual child who has already begun to abstract conceptual representations of her
two languages from clusters thereof. The child might incorporate the French word fiche
(homophonous with fish but meaning “card”) into the French rather than English cluster
HOW BILINGUALS PERCEIVE SPEECH
42
based at least in part on a conceptual understanding that the speaker who was heard using this
word speaks only French.
4.4. Conclusion
To conclude, the present study challenges the view that bilingual listeners adjust
perception across languages as a deterministic function of their perceptual input. We
demonstrate for the first time that bilinguals can adjust to the speech signal based on higher-
level information in the form of conceptual knowledge about which language is being
spoken. In terms of a bilingual model focused specifically on listening, this finding suggests a
relatively complex architecture, insofar as it implicates a conceptual level of processing. In
terms of a more comprehensive bilingual model encompassing both listening and speaking,
however, this finding suggests a relatively simple architecture, in that conceptually-based
language selection is possible in both modalities. It is not the strict purview of the speaking
modality.
Appendix
In the main text we dealt with variance heterogeneity across language contexts by performing
WMW tests whose rank transformations eliminated detection of any such variance. An
arguably more cautious approach to dealing with variance heterogeneity would be to perform
an unpaired Welch’s t-test, which does not assume equal variances. We reported the results of
the WMW test because our raw data additionally exhibit departures from normality, and the
WMW test is the standard approach for dealing with non-normally distributed data. As
HOW BILINGUALS PERCEIVE SPEECH
43
alluded to already, however, the reason that the WMW test does not assume normality is that
it rank-transforms the data. In fact, when the Student’s t-test is performed on the same rank-
transformed data, its test statistic is a monotonically increasing function of that of the WMW
test (Conover & Iman, 1981), and the two tests rarely diverge on whether to reject the null
hypothesis (Zimmerman, 2012). This implies that the Welch’s t-test could replace the WMW
test as a distribution-free test if performed on the same rank-transformed data. Zimmerman
and Zumbo (1993; see also Ruxton, 2006) recommended precisely this approach for data like
ours exhibiting both variance heterogeneity and non-normality. We therefore performed a
two-tailed Welch’s t-test over each bilingual group’s rank-transformed data (Fig. 3), entering
context as the between-subjects factor (alpha set at .05). Mirroring our WMW test results,
each bilingual groups’ mean boundary rank differs significantly across contexts (Spanish-
English group: t(27) = 2.11, p = .0443; French-English group: t(25) = 2.61, p = .0147). Our
results thus hold with this arguably more cautious approach.
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Figure and Supplementary Data Captions
Figure 1. Spanish- and French-English bilinguals’ response probability functions, derived
from logistic regression. The left panel displays Spanish-English bilinguals’ median
probability of responding that they heard the beginning of the ostensible word pafri (rather
than bafri), plotted as a function of the language context and – continuum. The right
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panel displays French-English bilinguals’ median probability of responding that they heard
the beginning of the ostensible word pefru (rather than befru), plotted as a function of the
language context and <–< continuum (all error bars denote SEM).
Figure 2. Each bilingual group’s VOT boundary values within the two language contexts,
derived from logistic regression. Individual boundary values are represented by the gray
circles and context medians by the black circles (error bars denote SEM). Each participant’s
individual boundary value is the predicted point on the VOT dimension where he or she
becomes as likely to make a /p/- as a /b/-initial response. Some boundary values fall outside
the continuum tokens’ VOT range (i.e., −35 to +30 ms). They were not computationally
constrained to fall within this range for lack of any a priori basis for such a constraint on the
boundary values of individual listeners.
Figure 3. Each bilingual group’s boundary ranks within the two language contexts. Gray
circles represent individual boundary ranks and black circles context medians (error bars
denote SEM). Each participant's individual boundary rank represents the magnitude of his or
her boundary value relative to the boundary values of all other participants in the same
bilingual group across both contexts. Thus, the lowest boundary rank represents the lowest
boundary value, the second lowest boundary rank the second lowest boundary value, and so
on (equal ranks represent tied values).
Supplementary Data S1. CSV file of our data sets as displayed in Fig. 1–3.
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