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Lexical Effects on Spoken Word Recognition in Persian-
Speaking Preschool-Aged Children with Normal Hearing
Mohammad Majid Oryadi-Zanjania*
*E-mail: oryadim@gmail.com
aDepartment of Speech Therapy, School of Rehabilitation Sciences, Shiraz University of Medical Sciences, Abiverdi1, Chamran Blvd., P.O.
Box: 71345-1733, Shiraz, Iran, ORCID: 0000-0002-0366-967X
Abstract
The current study aimed to determine lexical effects on spoken word recognition in Persian-speaking
preschool-aged children with normal hearing. The research, as a cross-sectional study, was administered in sixty-
two 4-to-6-year-old children who were recruited using convenient sampling from a preschool center in Shiraz city,
Iran. The preschool version of the Persian Lexical Neighborhood Tests (PLNTs-PV) was used, including four
subscales. It has been demonstrated that word lexical difficulty and word length affected the Persian-speaking 4-to-
6-year-old children’s speech-in-noise performance. The PLNTs-PV can be used measuring speech-in-noise
recognition in Persian-speaking preschool-aged children. We recommend managing the environment’s noise as one
of the practical solutions to improve preschool-aged children’s speech recognition performance.
Keywords: Lexical neighborhood tests; speech perception; speech-in-noise recognition; hearing, Persian-speaking preschool-aged children
1. Introduction
Indeed, research evidence indicated that the essential issue in pediatric users of hearing aids (HAs) or cochlear
implants (CIs) is speech recognition under spectrally degraded conditions (Caldwell & Nittrouer, 2013; Ching et
al., 2018; Eisenberg et al., 2016; Mohammad Majid Oryadi-Zanjani & Vahab, 2021; Ren et al., 2018; Zaltz et al.,
2020). To deal with the issue, we need powerful assessment tools to detect not only the children's auditory
dysfunction in noise but also to determine the probably underlying cognitive processes (Kirk, Diefendorf, et al.,
1995; Kirk et al., 1998; Kirk & Hudgins, 2016; M. M. Oryadi-Zanjani & Zamani, 2020; Robbins & Kirk, 1996).
According to the findings of several studies on different populations, lexically controlled tests can reliably be used
to assess speech recognition performance in children with hearing loss (HL) and their peers with normal hearing
(NH) (Eisenberg et al., 2002; Holt et al., 2011; Kirk, Diefendorf, et al., 1995; Kirk et al., 2000; Kirk, Pisoni, et
al., 1995; Kirk et al., 2012; Krull et al., 2010; Lee & Sim, 2020; Mohammad Majid Oryadi-Zanjani, 2022;
Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-Zanjani & Zamani, 2020; Wang et al., 2010).
Moreover, the children's speech-in-noise (SiN) performance is variable under lexical effects (Kirk, Pisoni, et al.,
1995; Krull et al., 2010; Mohammad Majid Oryadi-Zanjani, 2023; Mohammad Majid Oryadi-Zanjani & Vahab,
2021; M. M. Oryadi-Zanjani & Zamani, 2020; Wang et al., 2010).
So far, lexical neighborhood tests have been developed to assess speech recognition performance in children
speaking in some different languages (Kirk et al., 1998; Krull et al., 2010; Lee & Sim, 2020; M. M. Oryadi-
Zanjani & Zamani, 2020; Wang et al., 2010). Accordingly, linguistic properties of the stimulus words and word
length, as two fundamental factors, affect spoken word recognition (SWR) under spectrally degraded conditions
(Kirk, Pisoni, et al., 1995; Krull et al., 2010; Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-
Zanjani & Zamani, 2020). But interestingly, the findings demonstrated that lexical effects on SWR may depend
on the children's language. Accordingly, in contrast to English (Kirk, Pisoni, et al., 1995; Krull et al., 2010) and
Persian (Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-Zanjani & Zamani, 2020), lexical
effects on Mandarin-speaking children with/without HL were just demonstrated in disyllabic words (Wang et al.,
2010). The participants' age range, however, was different in these studies, including 7-to-12 in Kirk et al.'s (Kirk,
Pisoni, et al., 1995), 5-to-12 in Krull et al.'s (Krull et al., 2010), 4-to-7 in Wang et al.'s (Wang et al., 2010), and 6-
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to-13 years in Oryadi-Zanjani et al.'s studies (Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-
Zanjani & Zamani, 2020).
As a result, considering the factor of age, there is a significant difference between the studies on Mandarin and
Persian in comparison with the English ones; that is a lack of school-aged children in Wang et al.'s (Wang et al.,
2010) and preschool-aged children in Oryadi-Zanjani et al.'s studies (Mohammad Majid Oryadi-Zanjani & Vahab,
2021; M. M. Oryadi-Zanjani & Zamani, 2020). Therefore, the findings may change if these age ranges are
included in the studies on Mandarin- and Persian-speaking children with HL and their peers with NH.
Furthermore, we need more studies to derive a definitive conclusion about the issue. Additionally, before studying
the SiN performance of Persian-speaking preschool-aged children with NH, we need to elicit the information of
their peers with NH using the Persian Lexical Neighborhood Tests (PLNTs).
In conclusion, the current study aimed to determine lexical effects on SWR in Persian-speaking preschool-aged
children with NH using the PLNTs. We hypothesized that both linguistic properties of the stimulus words and
word length affect the 4-to-6-year-old children’s SWR performance under spectrally degraded conditions.
2. Methods
The research was administered as a cross-sectional study. Informed consent was obtained from the parents of
the children participating in the study, and the research protocol was approved by the Ethics Committee of Shiraz
University of Medical Sciences, Shiraz, Iran (the approval number: IR.SUMS.REHAB.REC.1401.015). The aim
was to assess spoken word recognition in preschool-aged children with NH based on the Neighborhood Activation
Model by using the PLNTs (M. M. Oryadi-Zanjani & Zamani, 2020).
2.1 Participants
Sixty-two 4-to-6-year-old children [(four years = 20, five years = 21, six years = 21) (female = 36, male = 26)]
were recruited through convenient sampling from a preschool center in Shiraz City, Iran. The inclusion criteria
included: age, gender, Persian-speaking, normal hearing thresholds, regular communication, speech skills,
language skills, and no additional handicapping conditions. Each child’s health status was verified according to
the child’s preschool health case and the teacher/parent’s report.
2.2 Assessment tool
Oryadi-Zanjani et al. developed a lexically controlled assessment toolkit (4 subscales) entitled the Persian
Lexical Neighborhood Tests (PLNTs) based on the Neighborhood Activation Model to measure spoken word
recognition (SWR) in Persian-speaking children, which includes: The Persian Monosyllabic Lexical
Neighborhood Tests (the PMLNT-easy [18 words], the PMLNT-hard [27 words]) and the Persian Disyllabic
Lexical Neighborhood Test (the PDLNT-easy [18 words], the PDLNT-hard [27 words]). The PLNTs were
administered to 33 school-aged children with HL and 20 of their peers with NH. They concluded that the PLNTs
are a useful language-independent tool to assess the SWR of children with/without HL under spectrally degraded
conditions (Mohammad Majid Oryadi-Zanjani, 2023; Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M.
Oryadi-Zanjani & Zamani, 2020).
The number of test words was reduced to adapt the PLNTs to preschool-aged children’s competency.
Accordingly, the preschool version of the PLNTs (PLNTs-PV) includes The Persian Monosyllabic Lexical
Neighborhood Tests (the PMLNT-easy [10 words], the PMLNT-hard [10 words]) and the Persian Disyllabic
Lexical Neighborhood Test (the PDLNT-easy [11 words], the PDLNT-hard [11 words]). Therefore, the PLNTs-
PV could administer quickly with minimal children's exhaustion.
2.3 Procedure
The experiments were administered using headphones at a preschool center because there was no adjusted
acoustic room. Microsoft PowerPoint software was used to present the stimuli through a PC or Laptop.
Accordingly, 12 subtests were administered based on SNRs levels. The signal-to-noise ratios (SNRs) of 0, 4, and
15 dB were chosen to make sure that floor or ceiling effects would not affect the children’s performance (Table
1).
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Table 1: The characteristics of the subtests
Subtests
0 dB
4 dB
15 dB
PMLNT-easy
X1
X2
X3
PDLNT-easy
X4
X5
X6
PMLNT-hard
X7
X8
X9
PDLNT-hard
X10
X11
X12
First, a training pretest was administered using eight practice words in the 4 dB SNR through auditory modality
including two monosyllabic easy, two monosyllabic hard, two disyllabic easy, and two disyllabic hard. Two
trained undergraduate students administered the experiments as the examiners. Examiner 1 sat near the participant
to carry out each test on the PC or Laptop. She played each auditory, visual, or audiovisual file, and then the
participant should repeat the word. Examiner 2 sat behind the children to transcript what was repeated by them.
Each test item was played once but repeated one more time if needed. A short rest took after each subtest. The
test was stopped after five consecutive or ten different failures to repeat the words to prevent any adverse
psychological effects on the children. The children’s scores on each subscale were calculated based on the number
of words repeated correctly divided by the total number of words. The data were analyzed using IBM SPSS version
23.
3. Results
3.1 Effect of lexical difficulty on spoken word recognition
To investigate the effect of lexical difficulty on the SWR, the children’s mean scores compared between the
PMLNT-easy versus the PMLNT-hard and the PDLNT-easy versus the PDLNT-hard by the Independent-Samples
T-Test (Table 2). Accordingly, a significant difference was found in the children’s SWR performance using the
PDLNT-easy and the PDLNT-hard in all the SNRs; that is, the children’s performance on the disyllabic easy
words was better than their performance on the disyllabic hard words. But, regarding the PMLNT-easy and the
PMLNT-hard, although the children’s scores of the easy monosyllabic words were higher than the hard
monosyllabic words in all the SNRs, the difference was significant just in 4 dB SNR. Therefore, the children’s
SWR performance can be variable according to word length and lexical difficulty under spectrally degraded
conditions (Figure).
Table 2: Comparison of the scores means of children with normal hearing between subscales based on lexical difficulty
Word length
SNR (dB)
Lexical difficulty
N
Mean
Standard deviation
P
Monosyllabic
0
Easy
62
4.741
2.071
> 0.05
Hard
62
4.322
1.998
4
Easy
62
6.822
2.044
< 0.01
Hard
62
5.790
1.590
15
Easy
62
8.419
2.092
> 0.05
Hard
62
8.000
1.717
Disyllabic
0
Easy
62
7.516
1.973
< 0.01
Hard
62
5.500
1.956
4
Easy
62
9.016
2.176
< 0.01
Hard
62
6.871
1.979
15
Easy
62
9.612
1.813
< 0.01
Hard
62
8.290
1.786
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Figure: Children's scores in subscales based on SNR levels
3.2 Effect of word length on spoken word recognition
To investigate the effect of word length on the SWR, the children’s mean scores compared between the
PMLNT-easy versus the PDLNT-easy and the PMLNT-hard versus the PDLNT-hard by the Independent-Samples
T-Test (Table 3). Accordingly, a significant difference was found in the children’s SWR performance using the
PMLNT-easy and the PDLNT-easy in all the SNRs; that is, the children’s performance on the easy disyllabic
words was better than their performance on the easy monosyllabic words. But, regarding the PMLNT-hard and
the PDLNT-hard, although the children’s scores of the disyllabic hard words were higher than the monosyllabic
hard words in all the SNRs, the difference was significant in 0 dB and 4 dB SNR. Therefore, word length affected
the children’s SWR performance under spectrally degraded conditions (Figure).
Table 3: Comparison of the scores means of children with normal hearing between subscales based on word length
Word length
SNR (dB)
Lexical difficulty
N
Mean
Standard deviation
P
Easy
0
Monosyllabic
62
4.741
2.071
< 0.01
Disyllabic
62
7.516
1.973
4
Monosyllabic
62
6.822
2.044
< 0.01
Disyllabic
62
9.016
2.176
15
Monosyllabic
62
8.419
2.092
< 0.01
Disyllabic
62
9.612
1.813
Hard
0
Monosyllabic
62
4.322
1.998
< 0.01
Disyllabic
62
5.500
1.956
4
Monosyllabic
62
5.790
1.590
< 0.01
Disyllabic
62
6.871
1.979
15
Monosyllabic
62
8.000
1.717
> 0.05
Disyllabic
62
8.290
1.786
3.3 Effect of Signal-to-Noise Ratio Levels on spoken word recognition
To investigate the effect of SNR levels on the SWR, the children’s mean scores of each PLNTs subscale were
compared among the different SNRs by the Repeated Measures ANOVA (Table 4). Accordingly, using
Bonferroni correction, there was a significant difference in the children’s PLNTs scores under spectrally degraded
conditions from 0 to 15 dB SNR (Figure). The children’s SWR performance improved entirely with increasing
the SNR level.
0
1
2
3
4
5
6
7
8
9
10
0 dB 4 dB 15 dB
Children's scores
SNR levels (dB)
PDLNT-easy PDLNT-hard PMLNT-easy PMLNT-hard
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Table 4: Comparison of the scores means between children with normal hearing based on SNR
Lexical difficulty
Word length
N
0 vs. 4 dB
4 vs. 15 dB
0 vs. 15 dB
P
P
P
Easy
Mono
62
< 0.01
< 0.01
< 0.01
Di
62
< 0.01
< 0.05
< 0.01
Hard
Mono
62
< 0.01
< 0.01
< 0.01
Di
62
< 0.01
< 0.01
< 0.01
3.4 Effect of sex on spoken word recognition
As shown in Table 5, the children’s mean scores of the PLNTs were compared between the girls and the boys
in all the SNRs by the Independent-Samples T-Test. Hence, no significant difference was found in SWR
performance between them.
Table 5: Comparison of the scores means of children with normal hearing between subscales based on sex
Word length
SNR (dB)
Lexical difficulty
Sex
N
Mean
Standard deviation
P
Easy
0
Monosyllabic
Female
36
4.916
2.143
> 0.05
Male
26
4.500
1.984
Disyllabic
Female
36
7.694
1.924
> 0.05
Male
26
7.269
2.050
4
Monosyllabic
Female
36
7.166
2.021
> 0.05
Male
26
6.346
2.018
Disyllabic
Female
36
9.277
1.733
> 0.05
Male
26
8.846
2.411
15
Monosyllabic
Female
36
8.722
1.861
> 0.05
Male
26
7.961
2.391
Disyllabic
Female
36
9.777
1.333
> 0.05
Male
26
9.461
2.213
Hard
0
Monosyllabic
Female
36
4.416
2.075
> 0.05
Male
26
3.923
1.853
Disyllabic
Female
36
5.666
1.912
> 0.05
Male
26
5.346
2.058
4
Monosyllabic
Female
36
5.777
1.456
> 0.05
Male
26
5.730
1.778
Disyllabic
Female
36
7.111
1.878
> 0.05
Male
26
6.769
1.773
15
Monosyllabic
Female
36
7.972
1.482
> 0.05
Male
26
8.000
2.059
Disyllabic
Female
36
8.638
1.606
> 0.05
Male
26
7.961
1.865
4. Discussion
According to the findings, the preschool version of the PLNTs (PLNTs-PV) could use assessing Persian-
speaking 4-to-6-year-old children’s SWR performance. The PLNTs-PV, as the shorter form of the PLNTs (M. M.
Oryadi-Zanjani & Zamani, 2020) with fewer items, includes the PMLNT-easy [10 words], the PMLNT-hard [10
words], the PDLNT-easy [10 words], and the PDLNT-hard [10 words]. Thus, it could use testing young children’s
speech recognition by spending less time and energy. In addition, The PLNTs-PV, as a lexically controlled test,
has been presented to assess Persian-speaking preschool-aged children’s SiN skills for the first time (Mohammad
Majid Oryadi-Zanjani, 2022).
Using the PLNTs-PV, it has generally been demonstrated that word lexical difficulty and word length affected
the Persian-speaking 4-to-6-year-old children’s SiN performance. The children’s SWR performance improved
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entirely with increasing the SNR level from 0 dB to 15 dB, similar to the findings of the previous studies
(Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-Zanjani & Zamani, 2020). Therefore, it can
be derived that reducing environmental noise may be one of the essential solutions to improve children’s speech
recognition performance. Furthermore, it found that lexical effects operate on the speech recognition process
regardless of the children’s sexuality, consistent with the previous findings (Eisenberg et al., 2002; Kirk et al.,
1998; Kirk et al., 2000; Mohammad Majid Oryadi-Zanjani et al., 2021; Mohammad Majid Oryadi-Zanjani &
Vahab, 2021; Wang et al., 2010),
According to the Neighborhood Activation Model (Luce, 1986), the results showed that easy words are
recognized with greater accuracy than hard words by 4-to-6-year-old children; that is, organizing and accessing
spoken words from long-term lexical memory are influenced by both word frequency and acoustic-phonetic
similarity of other words from 4 years of age. Accordingly, unlike Mandarin-speaking 4-to-7-year-old children
(Wang et al., 2010), lexical effects on SWR were demonstrated among both monosyllabic and disyllabic words,
similar to the findings related to Persian-speaking 6-to-13-year-old children (Mohammad Majid Oryadi-Zanjani
& Vahab, 2021; M. M. Oryadi-Zanjani & Zamani, 2020) and English-speaking-5-to-14 year-old children
(Eisenberg et al., 2002; Kirk et al., 1998; Kirk et al., 2000; Kirk, Pisoni, et al., 1995; Krull et al., 2010). Thus,
lexical effects affect SWR performance regardless of children’s age range.
Following the findings of the previous studies, it found that the 4-to-6-year-old children with NH could
recognize the spoken disyllabic words with greater accuracy than the monosyllabic ones under spectrally degraded
conditions (Eisenberg et al., 2002; Kirk et al., 1998; Kirk et al., 2000; Kirk, Pisoni, et al., 1995; Krull et al., 2010;
Mohammad Majid Oryadi-Zanjani & Vahab, 2021; M. M. Oryadi-Zanjani & Zamani, 2020; Wang et al., 2010).
This finding confirms that lexical effects are most likely to account for the difference in preschool-aged children’s
performance on the SWR as a function of word length; That is, disyllabic words have relatively less lexical
neighborhood densities and more linguistic redundancy than monosyllabic words (Kirk et al., 2000).
Finally, 4 dB SNR may be the optimal SNR to examine preschool-aged children’s SWR performance. Because
0 dB SNR may be too demanding and 15 dB SNR may be too easy to investigate lexical effects on the speech
recognition process under spectrally degraded conditions.
In conclusion, linguistic properties of the stimulus words and word length affect the 4-to-6-year-old children’s
SWR performance under spectrally degraded conditions. Therefore, the PLNTs-PV as a lexically controlled test
independent of vocabulary and language competency can be used to measure SiN recognition in Persian-speaking
4-to-6-year-old children. For future research, cross-sectional studies are planned which will use the PLNTs-PV:
(I) to measure SWR performance in Persian-speaking preschool-aged children with HL; and (II) to compare
visual, auditory, and audiovisual SWR performance in Persian-speaking preschool-aged children with HL with
their typical peers.
5. Conclusion
Using the PLNTs-PV as a quick form of the PLNTs, it has been demonstrated that both linguistic properties of
the stimulus words and word length affect the Persian-speaking preschool-aged children’s spoken word
recognition performance under spectrally degraded conditions. Therefore, the PLNTs-PV, as a lexically controlled
assessment toolkit independent of vocabulary and language competency, can be used measuring speech-in-noise
recognition in Persian-speaking preschool-aged children. We recommend managing the environment’s noise as
one of the practical solutions to improve preschool-aged children’s speech recognition performance.
Acknowledgements
The authors would like to thank the undergraduate students for their valuable general assistant, Dr. E. Sadeghi,
for his careful statistical advice. Special thanks are expressed to the families and children who participated in the
research.
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Mohammad Majid Oryadi-Zanjani / International Journal of Research Publications (IJRP.ORG)
