American English Speakers Research Articles

Strategic Deception in Interlanguage Pragmatics: A Comparative Study on Chinese EFL Learners and Native Speakers of American English

Strategic Deception in Interlanguage Pragmatics: A Comparative Study on Chinese EFL Learners and Native Speakers of American English

Direct articulatory observation reveals phoneme recognition performance characteristics of a self-supervised speech model

Variability in speech pronunciation is widely observed across different linguistic backgrounds, which impacts modern automatic speech recognition performance. Here, we evaluate the performance of a self-supervised speech model in phoneme recognition using direct articulatory evidence. Findings indicate significant differences in phoneme recognition, especially in front vowels, between American English and Indian English speakers. To gain a deeper understanding of these differences, we conduct real-time MRI-based articulatory analysis, revealing distinct velar region patterns during the production of specific front vowels. This underscores the need to deepen the scientific understanding of self-supervised speech model variances to advance robust and inclusive speech technology.

The role of L1-dialect in L2 production

Abstract This study compared the productions of American English (AE) vowels /i/, /u/, /ɛ/, /ɔ/, /ɪ/, /æ/, /ʊ/, /ʌ/, and /ɑ/ between speakers of two Chinese dialects, the Leshan dialect (LSd) and the Xining dialect (XNd). The participants were native speakers of XNd (n = 120) and LSd (n = 120) with advanced English proficiency. Their vowel productions were compared with those of 22 native AE speakers. The results showed that (1) XNd and LSd participants significantly differed in F1 and/or F2 from AE participants when producing /ɪ/, /æ/, /ʌ/, and /ʊ/ and /ɪ/, /ɑ/, /ɔ/, and /ʌ/, respectively; (2) compared with AE participants, XNd participants had significantly longer durations of /ɪ/, /ʊ/, /ʌ/, /ɛ/, and /æ/, and LSd participants had significantly longer durations of /ɪ/, /ʌ/, and /ɛ/. Overall, the vowels that differed in production from that of native speakers were absent in both the L1 dialects and L1 of participants.

Temporal Coordination of Articulatory Gestures in Nonnative Onset Clusters: Evidence From American English Speakers Using Electromagnetic Articulography.

Research in cross-language speech production indicates that, although the production of nonnative consonant clusters is often difficult, speakers of American English can produce some nonnative clusters (e.g., /fn/) with high accuracy. This ease of production for select nonnative clusters may occur due to similarity of phonetic structure with native clusters (e.g., nonnative /fn/ and native /sm/ are both fricative-nasal sequences). The current study tested this hypothesis by examining the extent of transfer of articulatory coordination from phonetically similar native onset clusters (i.e., /fl/, /sm/) to nonnative /fn/ clusters. Using electromagnetic articulography, lip, tongue, and jaw movements were recorded in nine participants during the production of 22 nonwords (eight tokens per nonword) containing the native and nonnative clusters in different carrier phrases. We examined the temporal lags between each consonantal gesture in a cluster and the flanking vowel gesture, which were compared to the matched singleton conditions. Analyses revealed that, as in native speech, when the syllable onset became more complex (i.e., CV ➔ CCV [C as consonant, V as vowel]), there was an increase in lag (less temporal overlap) between the leftmost consonantal gesture and the vocalic gesture, whereas there was a decrease in lag (more temporal overlap) between the rightmost consonant and the vocalic gesture (i.e., C-center timing). However, the segmental makeup of the cluster and type of carrier phrase used were also found to influence this change in temporal organization, raising new questions for future research. By and large, the findings are in agreement with the idea that the temporal coordination of articulator movements may be transferred from native clusters to phonetically similar nonnative clusters. However, kinematic measures of a broader range of nonnative clusters in different contexts are needed to fully explore this position.

An Innovative Approach to Determine Programmed Intermittent Epidural Bolus Pump Settings for Labor Analgesia: A Randomized Controlled Trial.

Three settings are required on a programmed intermittent epidural bolus (PIEB) pump for labor analgesia: the PIEB next bolus (PIEBnb), PIEB interval (PIEBi), and PIEB volume (PIEBv). The ideal settings for these parameters are still unknown. We hypothesized a mathematical modeling tool, response surface methodology (RSM), could estimate 3 PIEB pump parameters while balancing 3 clinically important patient outcomes simultaneously. The study objective was to use RSM to estimate PIEB settings (PIEBnb, PIEBi, and PIEBv) while maximizing maternal satisfaction, minimizing the need for clinician-administered boluses, and optimizing the ratio of delivered/requested patient-controlled epidural analgesia (PCEA) boluses simultaneously. With institutional ethics approval, a double-blind randomized trial was completed in a tertiary care labor and delivery center. Nulliparous, English-speaking American Society of Anesthesiologists (ASA) physical status II patients aged 18 to 45 years at full term, single gestation in vertex presentation, in spontaneous labor and ≤7 cm cervical dilation were included. Patients with comorbidities, contraindications to neuraxial analgesia, using chronic analgesics, <152 cm, or body mass index (BMI) >45 kg/m 2 were excluded. After informed consent, labor analgesia was initiated using 10 mL ropivacaine 0.2% with 10 µg/mL fentanyl solution and PCEA (volume 6 mL every 10 minutes). Patients were randomized to predetermined PIEB settings. RSM identified 3 pump settings that represented a stationary point that best maximized or minimized 3 outcomes simultaneously: PCEA ratio (a ratio closest to 1), clinician bolus (optimal is 0), and maternal satisfaction (visual analog scale, 0-100, ideal response is ≥90). Of 287 potential participants, 192 did not meet inclusion criteria or declined to participate, and 26 were withdrawn, leaving 69 patients for study inclusion. Using RSM, the suggested PIEB settings for all the primary study outcomes were as follows: PIEBnb = 29.4 minutes, PIEBi = 59.8 minutes, and PIEBv = 6.2 mL. These PIEB settings corresponded to the following clinical outcomes: maternal satisfaction at 93.9%, PCEA ratio at 0.77, and need for clinician bolus at 0.29. The dermatome sensory score was between T10 and T5 in 89% of the patients. The median lowest Bromage score was 4. This novel study used a mathematical model to estimate PIEB pump settings while simultaneously maximizing 3 clinical outcomes. Equally weighted clinical outcomes prevent maximal outcome optimization and may not reflect patient priorities. Future studies or quality improvement endeavors could use RSM methodology to estimate PIEB pump settings targeting optimal values for a single clinical outcome of determined importance to parturients.

Cognitive load associated with speaking clearly in reverberant rooms

Communication is a fundamental aspect of human interaction, yet many individuals must speak in less-than-ideal acoustic environments daily. Adapting their speech to ensure intelligibility in these varied settings can impose a significant cognitive burden. Understanding this burden on talkers has significant implications for the design of public spaces and workplace environments, as well as speaker training programs. The aim of this study was to examine how room acoustics and speaking style affect cognitive load through self-rating of mental demand and pupillometry. Nineteen adult native speakers of American English were instructed to read sentences in both casual and clear speech—a technique known to enhance intelligibility—across three levels of reverberation (0.05 s, 1.2 s, and 1.83 s at 500–1000 Hz). Our findings revealed that speaking style consistently affects the cognitive load on talkers more than room acoustics across the tested reverberation range. Specifically, pupillometry data suggested that speaking in clear speech elevates the cognitive load comparably to speaking in a room with long reverberation, challenging the conventional view of clear speech as an ‘easy’ strategy for improving intelligibility. These results underscore the importance of accounting for talkers' cognitive load when optimizing room acoustics and developing speech production training.

AI generates covertly racist decisions about people based on their dialect

Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4–7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.

Machine Learning Recognizes Frequency-Following Responses in American Adults: Effects of Reference Spectrogram and Stimulus Token.

Electrophysiological research has been widely utilized to study brain responses to acoustic stimuli. The frequency-following response (FFR), a non-invasive reflection of how the brain encodes acoustic stimuli, is a particularly propitious electrophysiologic measure. While the FFR has been studied extensively, there are limitations in obtaining and analyzing FFR recordings that recent machine learning algorithms may address. In this study, we aimed to investigate whether FFRs can be enhanced using an "improved" source-separation machine learning algorithm. For this study, we recruited 28 native speakers of American English with normal hearing. We obtained two separate FFRs from each participant while they listened to two stimulus tokens /i/ and /da/. Electroencephalographic signals were pre-processed and analyzed using a source-separation non-negative matrix factorization (SSNMF) machine learning algorithm. The algorithm was trained using individual, grand-averaged, or stimulus token spectrograms as a reference. A repeated measures analysis of variance revealed that FFRs were significantly enhanced (p < .001) when the "improved" SSNMF algorithm was trained using both individual and grand-averaged spectrograms, but not when utilizing the stimulus token spectrogram. Similar results were observed when extracting FFRs elicited by using either stimulus token, /i/ or /da/. This demonstration shows how the SSNMF machine learning algorithm, using individual and grand-averaged spectrograms as references in training the algorithm, significantly enhanced FFRs. This improvement has important implications for the obtainment and analytical processes of FFR, which may lead to advancements in clinical applications of FFR testing.

Speaker-independent speech inversion for recovery of velopharyngeal port constriction degreea).

For most of his illustrious career, Ken Stevens focused on examining and documenting the rich detail about vocal tract changes available to listeners underlying the acoustic signal of speech. Current approaches to speech inversion take advantage of this rich detail to recover information about articulatory movement. Our previous speech inversion work focused on movements of the tongue and lips, for which "ground truth" is readily available. In this study, we describe acquisition and validation of ground-truth articulatory data about velopharyngeal port constriction, using both the well-established measure of nasometry plus a novel technique-high-speed nasopharyngoscopy. Nasometry measures the acoustic output of the nasal and oral cavities to derive the measure nasalance. High-speed nasopharyngoscopy captures images of the nasopharyngeal region and can resolve velar motion during speech. By comparing simultaneously collected data from both acquisition modalities, we show that nasalance is a sufficiently sensitive measure to use as ground truth for our speech inversion system. Further, a speech inversion system trained on nasalance can recover known patterns of velopharyngeal port constriction shown by American English speakers. Our findings match well with Stevens' own studies of the acoustics of nasal consonants.

Tracking age-related changes in voice and speech production with Landmark-based analysis of speech.

Voice and speech production change with age, which can lead to potential communication challenges. This study explored the use of Landmark-based analysis of speech (LMBAS), a knowledge-based speech analysis algorithm based on Stevens' Landmark Theory, to describe age-related changes in adult speakers. The speech samples analyzed were sourced from the University of Florida Aging Voice Database, which included recordings of 16 sentences from the Speech Perception in Noise test of Bilger, Rzcezkowski, Nuetzel, and Rabinowitz [J. Acoust. Soc. Am. 65, S98-S98 (1979)] and Bilger, Nuetzel, Rabinowitz, and Rzeczkowski [J. Speech. Lang. Hear. Res. 27, 32-84 (1984)]. These sentences were read in quiet environments by 50 young, 50 middle-aged, and 50 older American English speakers, with an equal distribution of sexes. Acoustic landmarks, specifically, glottal, bursts, and syllabicity landmarks, were extracted using SpeechMark®, MATLAB Toolbox version 1.1.2. The results showed significant age effect on glottal and burst landmarks. Furthermore, the sex effect was significant for burst and syllabicity landmarks. While the results of LMBAS suggest its potential in detecting age-related changes in speech, increase in syllabicity landmarks with age was unexpected. This finding may suggest the need for further refinement and adjustment of this analytical approach.

Estimates of speech efficiency in monolingual and bilingual speakers of English.

Introduction The Speech Efficiency Score (SES) serves as an acoustic metric for assessing fluency in conversational speech within the temporal domain. This study leverages SES to investigate conversational speech efficiency among native speakers of American English (AE) compared to speakers of Mandarin-accented English (MAE). Methods SES, speaking rate, articulation rate, and vocabulary diversity were measured and compared between two groups: native AE speakers and MAE speakers. The study utilized conversational speech samples collected from both groups to analyze these metrics. Results Findings indicate a disparity in speaking rate and articulation rate between the AE and MAE groups, with the AE group exhibiting significantly faster speech. However, no significant differences were observed in SES and vocabulary diversity between the two groups. Conclusion The results are discussed in the context of the interplay between speaking rate, speech fluency, and vocabulary diversity. These findings shed light on the maintenance of speech efficiency among bilingual speakers, suggesting that despite differences in speaking rate and articulation rate, SES and vocabulary diversity remain comparable between native AE speakers and MAE speakers. .

Expressing smells in (American) English

Abstract The paper reports on a study of the usage of smell verbs over the last 200 years by speakers of American English. The focus is on how the expression of smell changes over time and what this reveals about the way speakers conceptualize and assess smells. The study is based on usage data from the COHA (Corpus of Historical American English). They were quantitatively analysed employing the methods of simple and (multiple) distinctive collexeme analysis. The results of our investigations indicate both a general increase over time in the usage of smell-verb constructions and a noticeable diversification of the smell vocabulary used by American English speakers. Moreover, the results of the collexeme analyses reveal more detailed aspects of the types of smell descriptors people use in smell talk. Reflecting what kinds of smell emitters are most typically and especially closely associated with the individual smell-verb constructions at particular times, they are informative about the sources of smells that are salient enough in our culture and (well-)known enough in the speech community to be used as functional smell descriptors and how these may change over time.

African American Preschoolers' Performance on Norm-Referenced Language Assessments: Examining the Effect of Dialect Density and the Use of Scoring Modifications.

We investigated and compared the outcomes from two standardized, norm-referenced screening assessments of language (i.e., Clinical Evaluation of Language Fundamentals Preschool-Second Edition [CELFP-2], Diagnostic Evaluation of Language Variation-Screening Test [DELV-ST]) with African American preschoolers whose spoken dialect differed from that of General American English (GAE). We (a) described preschoolers' performance on the CELFP-2 Core Language Index (CLI) and its subtests with consideration of degree of dialect variation (DVAR) observed, (b) investigated how the application of dialect-sensitive scoring modifications to the expressive morphology and syntax Word Structure (WS) subtest affected CELFP-2 CLI scores, and (c) evaluated the screening classification agreement rates between the DELV-ST and the CELFP-2 CLI. African American preschoolers (N = 284) completed the CELFP-2 CLI subtests (i.e., Sentence Structure, WS, Expressive Vocabulary) and the DELV-ST. Density of spoken dialect use was estimated with the DELV-ST Part I Language Variation Status, and percentage of DVAR was calculated. The CELFP-2 WS subtest was scored with and without dialect-sensitive scoring modifications. Planned comparisons of CELFP-2 CLI performance indicated statistically significant differences in performance based on DELV-ST-determined degree of language variation groupings. Scoring modifications applied to the WS subtest increased subtest scaled scores and CLI composite standard scores. However, preschoolers who demonstrated strong variation from GAE continued to demonstrate significantly lower performance than preschoolers who demonstrated little to no language variation. Affected-status agreement rates between assessments (modified and unmodified CELFP-2 CLI scores and DELV-ST Part II Diagnostic Risk Status) were extremely low. The application of dialect-specific scoring modifications to standardized, norm-referenced assessments of language must be simultaneously viewed through the lenses of equity, practicality, and psychometry. The results of our multistage study reiterate the need for reliable methods of identifying risk for developmental language disorder within children who speak American English dialects other than GAE. https://doi.org/10.23641/asha.26017978.

The Acoustic Differences in the Production of English and Korean Lateral /l/in the Word-initial Position by American English and South-North Korean Speakers

The Acoustic Differences in the Production of English and Korean Lateral /l/in the Word-initial Position by American English and South-North Korean Speakers

How Compliments and Compliment Responses Differ for American and Chinese People on Instagram

This paper reports a qualitative study on complimenting behaviors and response strategies of American English speakers (AES) and Chinese speakers (CS). It explores how the two speech groups differ in their patterns of compliment and response behaviors on Instagram. There are 26 participants who have answered a questionnaire that asks them to rate certain statements and let them give examples of compliments and responses. This paper will discuss the interpretations of the questionnaire and link them to linguistic politeness in virtual contexts and second language learning. Some limitations regarding each step of the research are that the sample size is too small to generalize the result to a greater population and that some questions in the questionnaire were not carefully designed. Future research should take note of the limitations and avoid them as much as possible.

The influence of accent and device usage on perceived credibility during interactions with voice-AI assistants

Voice-AI assistants offer innovative ways for people to interact with technology, such as delivering search results through human-sounding voices. Unlike printed text, however, voices are associated with particular characteristics, such as accents, which have the potential to influence perceived credibility. Voice-AI assistants are also a relatively new phenomenon, and while people who use them frequently may be inclined to trust them, other people may not be. The current study investigated how voice accent and frequency-of-use affected users’ credibility assessments of search results delivered by voice-AI assistants. Participants, who were native speakers of American English and self-classified themselves according to how frequently they used voice-AI assistants, listened to statements produced by neural text-to-speech in either an American English or British English accent. They then rated the credibility of both the information content and the voice itself, along several dimensions. Results showed that in multiple conditions, participants perceived information delivered by British-accented voices as more credible than that delivered by American English-accented voices. Furthermore, frequency-of-use exerted a significant effect on perceived trustworthiness of a voice. These findings have implications for the ethical design of voice-AI systems, and for human-computer interaction more generally.

Navigating the climate change minefield: the influence of metaphor on climate doomism

Climate doomism is an increasing concern for climate change communication. In the United States, this opinion regarding anthropogenic climate change is now more prevalent than climate skepticism, and is the primary reason cited for opposition to climate action. Doomism is the belief that catastrophic warming of the planet is now inevitable, and that effective mitigation is impossible. The behaviors resulting from this view are comparable to the result of climate skepticism: doomism produces paralyzing eco-anxiety and subsequently inaction. Prior work has hypothesized that the rise in climate doomism and eco-anxiety is linked to climate change risk communication. This study investigates the possibility that the metaphoric language used to communicate the severity and urgency of climate change could inadvertently promote doomism. We employ a survey model to test the influence of metaphoric language on perception of urgency, feasibility, and individual agency in relation to the climate crisis. American English-speaking participants (N = 1,542) read a paragraph describing climate change either as a “cliff edge” or “minefield,” with human agency manipulated to be present or absent. Responses were considered to be doomist if they reported a high sense of urgency, paired with a low sense of feasibility and/or agency; this indicates they have a high awareness of the risks associated with the climate crisis, but a low belief that it will be addressed, and/or that their actions can produce meaningful change. Use of either metaphor improved perceived feasibility without a reduction in urgency, indicating that metaphor is an effective climate communication strategy for conveying risk without promoting doomism. However, metaphoric presentation is only effective when paired with human agency, suggesting that agency is a necessary component for successful metaphoric climate communication strategies.

Does Native Language Matter in Perceptual Ratings of Dysarthria?

Despite the general agreement that dysarthria characteristics are largely language-independent, few efforts have attempted a systematic comparison across languages. To examine the role of native languages in the perception of speech characteristics of dysarthria secondary to Parkinson's disease (PD), auditory-perceptual ratings of dysarthria, and confidence level of the judgments were compared between two listener groups: language-matched and language-crossed. A total of 60 listeners (35 native speakers of Korean and 25 native speakers of American English) estimated speech abnormality for 20 speech dimensions using a visual analog scale method for both language-matched and language-crossed speech stimuli. Speech stimuli were passage readings of the respective languages obtained from individuals with and without PD. For speech dimension ratings, eight of 20 speech dimensions revealed significant differences in response to PD speech between the two listener groups, for most of which, language-crossed listeners' estimation was lower (i.e., more impaired) than language-matched listeners. For confidence-level ratings, language-matched listeners were less confident in the ratings of speakers with PD compared to the language-crossed listeners. The data support both language-universal and language-specific aspects in perceiving dysarthria characteristics, such that native language plays a role, especially when rating articulatory- and rhythmic-related characteristics. The findings are discussed with respect to the role of linguistic information, such as phonetic inventories and prosodic structures, in perceiving dysarthria characteristics.

Making the Unseen Seen: The Role of Signaling and Novelty in Rating Metaphors

Comprehension of metaphorical expressions differs with their degree of novelty. Conventional metaphors are typically comprehended as easily as literal sentences, while novel metaphors are responded to less quickly than their conventional counterparts. However, the influence of metaphor signals on the interpretability and acceptability of sentences with metaphors, especially their potential interaction with novelty, remains an open question. We conducted six online experiments among 1,694 native speakers of American English to examine how interpretability and acceptability ratings of individually presented sentences were affected by metaphor novelty and different types of metaphor signals. Across all six experiments, we consistently found that novel metaphors decreased the interpretability and acceptability of sentences compared to both conventional metaphors and literal controls. Signals, on the contrary, did not impact the interpretability or acceptability of the sentences. Moreover, only in experiment 3b did we find an interaction between metaphor type and signals. Specifically, when a metaphor was marked by double signals (i.e., both lexical signals and a typographical signal were added around the metaphorical keywords) vs. no signals, acceptability of novel metaphors increased, but acceptability of conventional metaphors decreased. We hypothesize that the double signaling of novel metaphors marks their novelty, making them more acceptable. By contrast, the double signaling of conventional metaphors may have been perceived as redundant, leading to a lower acceptability.

African American English speakers' pitch variation and rate adjustments for imagined technological and human addressees.

This paper examines the adaptations African American English speakers make when imagining talking to a voice assistant, compared to a close friend/family member and to a stranger. Results show that speakers slowed their rate and produced less pitch variation in voice-assistant-"directed speech" (DS), relative to human-DS. These adjustments were not mediated by how often participants reported experiencing errors with automatic speech recognition. Overall, this paper addresses a limitation in the types of language varieties explored when examining technology-DS registers and contributes to our understanding of the dynamics of human-computer interaction.