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Estimated number of words spoken per day for female and male study participants across six samples. N = 396. Year refers to the year when the data collection started; duration refers to the approximate number of days participants wore the EAR; the weighted average weighs the respective sample group mean by the sample size of the group.
Source publication
Women are generally assumed to be more talkative than men. Data were analyzed from 396 participants who wore a voice recorder
that sampled ambient sounds for several days. Participants' daily word use was extrapolated from the number of recorded words.
Women and men both spoke about 16,000 words per day.
Citations
... Example: «Women speak three times more words than males every day». The number is 16,215 for women and 15,669 for men [12] and the female/male gap is not so big (it changes with age). Doubtless, brain sex differences exist, as shown by neuroscientists like Eliot et al. [13], but in their "highlight" resumé of the article they state: "Few male/female differences survive correction for brain size. ...
Androcentrism, the tendency to place the male gender at the helm of society, permeates the primary dimensions in which each of us perceives, processes, and understands her/himself, other people, and groups. The present paper reflects on some of the repercussions that androcentrism provokes in the social sphere. As its origins are lost in time, the solutions to be devised to counter it are difficult and all to be found. The author dwells, with examples, on some deleterious repercussions provoked by androcentrism in the educational, social, and biomedical research fields. To attenuate its effects a higher-order pro-social behavior is suggested. It includes the shifting from the anthropo/androcentric paradigm to the biocentric one, and a cosmopolitan ethics based on solidarity all to be imagined. Plus, the creation of more bridges between humanistic and scientific cultures. This is because discrimination or prejudice based on gender is high worldwide as shown by the debates among Western philosophers, social scientists, ethicists, moral theologians, and their feminist interlocutors. In the scientific sphere the progressive inclusion of women in fields like STEMM, where they are underrepresented, is fundamental, as they are a considerable asset.
... 184). Related to our first point, one key EAR-based study (Mehl et al., 2007) showed that, contrary to the stereotype that women are more talkative than men, women and men spoke roughly the same number of words per day. However, while Mehl's method "can provide ecological, behavioral criteria that are independent of self-report," and "help study psychologically important subtle and habitual behaviors" (Mehl, 2017, p. 186), CA and MCA have already contributed enormously to our understanding of these things and more. ...
This article reviews two related approaches—conversation analysis (CA) and membership categorization analysis (MCA)—to sketch a systematic framework for exposing how categories and categorial phenomena are (re)produced in naturally occurring social interaction. In so doing, we argue that CA and MCA address recent concerns about psychological methods and approaches. After summarizing how categories are typically theorized and studied, we describe the main features of a CA approach to categories, including how this differs from conventional psychology. We review the core domains of research in CA and how categories can be studied systematically in relation to the basic machinery of talk and other conduct in interaction. We illustrate these domains through examples from different settings of recorded naturally occurring social interaction. After considering the applications that have arisen from CA and MCA, we conclude by drawing together the implications of this work for psychological science.
... Saving E into Raw Text and Process All While saving E as the raw text and putting it into context is conceptually straightforward, it faces significant practical challenges. For instance, humans, are estimated to speak an average of 16k words per day [71], totaling hundreds of millions of words over a lifetime [8]. Consequently, current LLMs usually cannot process all past experiences. ...
Building a human-like system that continuously interacts with complex environments -- whether simulated digital worlds or human society -- presents several key challenges. Central to this is enabling continuous, high-frequency interactions, where the interactions are termed experiences. We refer to this envisioned system as the LifeSpan Cognitive System (LSCS). A critical feature of LSCS is its ability to engage in incremental and rapid updates while retaining and accurately recalling past experiences. We identify two major challenges in achieving this: (1) Abstraction and Experience Merging, and (2) Long-term Retention with Accurate Recall. These properties are essential for storing new experiences, organizing past experiences, and responding to the environment in ways that leverage relevant historical data. Unlike language models with continual learning, which typically rely on large corpora for fine-tuning and focus on improving performance within specific domains or tasks, LSCS must rapidly and incrementally update with new information from its environment at a high frequency. Existing technologies with the potential of solving the above two major challenges can be classified into four classes based on a conceptual metric called Storage Complexity, which measures the relative space required to store past experiences. Each of these four classes of technologies has its own strengths and limitations. Given that none of the existing technologies can achieve LSCS alone, we propose a novel paradigm for LSCS that integrates all four classes of technologies. The new paradigm operates through two core processes: Absorbing Experiences and Generating Responses.
... The outputs are aggregated at 30-s intervals, a technique that ensures minimal personal information is captured while still providing sufficient data for reliable coding. This approach has been extensively used in prior research (e.g., Mehl et al., 2007;Orena et al., 2020;Ram ırez-Esparza et al., 2009, Ram ırez-Esparza andGarc ıa-Sierra, 2014;Ram ırez-Esparza et al., 2017a,b). We then selected intervals for coding by removing those with zero adult words. ...
... From the remaining intervals, we chose about 70 intervals per day with the highest word count for behavioral coding. Previous research has shown that 70 intervals are representative of a full day recording (Mehl et al., 2007;Ram ırez-Esparza et al., 2012). Notably, no significant differences were observed between the average word counts within selected intervals across ...
Differences in acoustic environments have previously been linked to socioeconomic status (SES). However, it is crucial to acknowledge that cultural values can also play a significant role in shaping acoustic environments. The goal of this study was to investigate if social behaviors related to cultural heritage and SES could help us understand how Latinx and European college students in the U.S. have different acoustic environments. College students were given digital recorders to record their daily acoustic environments for two days. These recordings were used to (1) evaluate nearfield noise levels in their natural surroundings and (2) quantify the percentage of time participants spent on behavioral collectivistic activities such as socializing and interacting with others. Behavioral collectivism was examined as a mediator between cultural heritage, SES, and nearfield noise levels. Findings revealed that both SES and cultural heritage were associated with nearfield noise levels. However, behavioral collectivism mediated the relationship between culture and nearfield noise levels. These findings show that collectivist cultural norms significantly relate to Latinx' daily noise levels. The implications of these findings for public health and health inequities included promoting equitable auditory well-being and better knowledge of socio-cultural settings.
... The Mehl et al. study published in 2007 that involved over 186 men and 210 women determined that the average number of words pronounced per day is 15,934, with a standard deviation (STD) of 7967 [23]. Assuming an average sentence length of 10 words (STD = 5) [24] and considering that the jaw opens and closes at least once per sentence, this results in an additional 1600 mastication cycles. ...
Scavenging energy from the earcanal’s dynamic motion during jaw movements may be a practical way to enhance the battery autonomy of hearing aids. The main challenge is optimizing the amount of energy extracted while working with soft human tissues and the earcanal’s restricted volume. This paper proposes a new energy harvester concept: a liquid-filled earplug which transfers energy outside the earcanal to a generator. The latter is composed of a hydraulic amplifier, two hydraulic cylinders that actuate a bistable resonator to raise the source frequency while driving an amplified piezoelectric transducer to generate electricity. The cycling of the resonator is achieved using two innovative flexible hydraulic valves based on the buckling of flexible tubes. A multiphysics-coupled model is established to determine the system operation requirements and to evaluate its theoretical performances. This model exhibits a theoretical energy conversion efficiency of 85%. The electromechanical performance of the resonator coupled to the piezoelectric transducer and the hydraulic behavior of the valves are experimentally investigated. The global model was updated using the experimental data to improve its predictability toward further optimization of the design. Moreover, the energy losses are identified to enhance the entire proposed design and improve the experimental energy conversion efficiency to 26%.
... When Vlad shared that Ilene tended to talk about four times more than he did, she agreed, immediately grounding her role as "the talker" in purported research findings that suggest women talk at least twice as much as men do. Though multiple studies have decidedly disconfirmed this relationship between gender and language (e.g., Cameron, 1997;Hyde, 2007;Mehl et al., 2007), the popularized notion that women speak more than men seemed to constitute a "scientific" point of reference for Ilene and Vlad. Though they joked about their differences, moreover, Ilene and Vlad highlighted parallels in the way they think about politics, religion, and popular culture, including the fact they both oriented to an overall rational, scientific approach eschewing religion. ...
Drawing on linguistic and biocultural anthropological perspectives on embodiment, this paper advances a “biolinguistic” approach to ethnographic research on intimacy, attending simultaneously to the co‐constitutive interactive, psychophysiological, and phenomenological processes that emerge in everyday embodied interaction between long‐term, cohabitating romantic partners. Through concurrent attention to natural interactions captured during video ethnography and moment‐to‐moment shifts in heart‐rate variability, this study complements and complicates existing psychological, communication, and anthropological research on intimacy. Three case‐studies of long‐term couples residing in the Southeastern United States demonstrate how neither pure psychophysiology nor pure linguistic analysis fully encapsulates potential patterns of intimacy among them. Rather, this microanalytical, biolinguistic approach to the complexities of body and language interplay, in treating embodiment and interaction as bidirectional phenomena, emphasizes that meanings and enactments of intimacy might look different for each couple and can change over time in complex ways that index couples’ enduring orientations towards various cultural and relational norms.
... The aerosols concentration emitted during case's breathing and 1 min h −1 talking was used as C a (m −3 ) considering that the infected case talked for 1 min h −1 . People speak about 16,000 words per day in 17 h (Mehl et al., 2007). The average speech rate for conversation of young adult and middle aged ranged in age from 21 to 64 years was 168.4 words per minute (Duchin & Mysak, 1987). ...
Simulated exposure to severe acute respiratory syndrome coronavirus 2 in the environment was demonstrated based on the actual coronavirus disease 2019 cluster occurrence in an office, with a projected risk considering the likely transmission pathways via aerosols and fomites. A total of 35/85 occupants were infected, with the attack rate in the first stage as 0.30. It was inferred that the aerosol transmission at long‐range produced the cluster at virus concentration in the saliva of the infected cases on the basis of the simulation, more than 10 ⁸ PFU mL ⁻¹ . Additionally, all wearing masks effectiveness was estimated to be 61%–81% and 88%–95% reduction in risk for long‐range aerosol transmission in the normal and fit state of the masks, respectively, and a 99.8% or above decline in risk of fomite transmission. The ventilation effectiveness for long‐range aerosol transmission was also calculated to be 12%–29% and 36%–66% reductions with increases from one air change per hour (ACH) to two ACH and six ACH, respectively. Furthermore, the virus concentration reduction in the saliva to 1/3 corresponded to the risk reduction for long‐range aerosol transmission by 60%–64% and 40%–51% with and without masks, respectively.
... Vulgarity or obscenity with regards to language refers to terms used to describe the use of vulgar language, such as swearing, taboo words, or offensive expressions [12,13]. Unfortunately, such language has become more and more common in contemporary culture [14], especially on social media sites like Twitter [15]. The majority of the time, however, vulgar language is used in the context of online harassment and negativity. ...
The proliferation of the internet, especially on social media platforms, has amplified the prevalence of cyberbullying and harassment. Addressing this issue involves harnessing natural language processing (NLP) and machine learning (ML) techniques for the automatic detection of harmful content. However, these methods encounter challenges when applied to low-resource languages like the Chittagonian dialect of Bangla. This study compares two approaches for identifying offensive language containing vulgar remarks in Chittagonian. The first relies on basic keyword matching, while the second employs machine learning and deep learning techniques. The keyword-matching approach involves scanning the text for vulgar words using a predefined lexicon. Despite its simplicity, this method establishes a strong foundation for more sophisticated ML and deep learning approaches. An issue with this approach is the need for constant updates to the lexicon. To address this, we propose an automatic method for extracting vulgar words from linguistic data, achieving near-human performance and ensuring adaptability to evolving vulgar language. Insights from the keyword-matching method inform the optimization of machine learning and deep learning-based techniques. These methods initially train models to identify vulgar context using patterns and linguistic features from labeled datasets. Our dataset, comprising social media posts, comments, and forum discussions from Facebook, is thoroughly detailed for future reference in similar studies. The results indicate that while keyword matching provides reasonable results, it struggles to capture nuanced variations and phrases in specific vulgar contexts, rendering it less robust for practical use. This contradicts the assumption that vulgarity solely relies on specific vulgar words. In contrast, methods based on deep learning and machine learning excel in identifying deeper linguistic patterns. Comparing SimpleRNN models using Word2Vec and fastText embeddings, which achieved accuracies ranging from 0.84 to 0.90, logistic regression (LR) demonstrated remarkable accuracy at 0.91. This highlights a common issue with neural network-based algorithms, namely, that they typically require larger datasets for adequate generalization and competitive performance compared to conventional approaches like LR.
... Furthermore, they avoid 1 st person singular pronouns , past tenses, present tenses [23]. Additionally, openness people use fewer sleep-related words [15]; certainty words like sure, definite , long words, and etc. [24]; first person singular words like (my, I , me) , few articles (the , an ,a , a lot) , long words and present tense verbs and discrepancies like (would , should and could ) [20]. ...
للدوال الاجتماعية أهمية كبيرة يمكن استعمالها في تحديد هوية المتحدث وتصنيفه، وتعتمد هذه الدوال على الاختلافات بين الأفراد؛ فبزوال هذا الاختلاف لن يتم الكشف عن العلامات الاجتماعية وعلى سبيل المثال: في الدراما الإنجليزية يُظهر الكتاب المشاركين أو الممثلين كأمثلة لأشخاص في الحياة الواقعية، مما يعكس مشاكلهم الاجتماعية وقضاياهم السياسية من خلال لغتهم يُظهر الناس شخصياتهم من خلال سلوكهم في مواقف معينة ومن خلال هوياتهم الاجتماعية اعتمدت هذه الدراسة فقط على المؤشرات الاجتماعية التي قد يستعملونها في حديثهم الفوري؛ لتحديد نوع الشخصية التي ينتمون إليها، وتستعمل الشخصيات في مسرحية "الأسلحة والرجل" للمخرج برنارد شو إشارات الكلام للكشف عن مواقفهم النفسية، يُظهر ميلر في مسرحيته "موت بائع متجول" لجمهوره أيضًا كيف يمكن للظروف الاجتماعية السيئة أن تجعل الناس يستعملون الكثير من المشاعر السلبية التي من الممكن أن تحدد كيفية توظيف دوال اجتماعية بكثرة عن غيرها من الدوال.
... There is evidence for the syllable frequency effect in favor of stored syllable-sized gesture scores during phonetic encoding in language production alphabetic languages such as Dutch and English (Cholin et al., 2006(Cholin et al., , 2011Levelt & Wheeldon, 1994). Speech is one of the most practiced motor behaviors, and practice leads to the storage of motor programs (Laganaro, 2019;Mehl et al., 2007). This assumption especially holds true for Chinese, which has about 1,200 syllables when tones are included. ...
Syllable frequency effects in spoken word production have been interpreted as evidence that speakers store syllable-sized motor programmes for phonetic encoding in alphabetic languages such as English or Dutch. However, the cognitive mechanism underlying the syllable frequency effect in Chinese spoken word production remains unknown. To investigate the locus of the syllable frequency effect in spoken Chinese, this study used a picture–word interference (PWI) task in which participants were asked to name the picture while ignoring the distractor word. The design included two variables: the syllable frequency of the target words (high vs. low) and the phonological relationships between distractor and target words (shared atonic syllable or not; related vs. unrelated). We manipulated mixed token and type syllable frequency in Experiment 1, and token syllable frequency but controlled type syllable frequency in Experiment 2. The results showed a facilitation effect of mixed syllable frequency and a similar facilitation effect of token syllable frequency. Importantly, the syllable frequency effect was found to be independent of the phonological facilitation effect. These results suggest that token syllable frequency played a dominant role in the observed facilitation effect, providing evidence that the syllable frequency effect arises in the phonetic encoding of Chinese spoken word production.
