This study investigated the effect of different types of phonetic training on potential changes in the production and perception of English vowels by Arabic learners of English. Forty-six Arabic learners of English were randomly assigned to one of three high variability vowel training programs: Perception training (High Variability Phonetic Training), Production training, and a Hybrid Training program (production and perception training). Pre- and post-tests (vowel identification, category discrimination, speech recognition in noise, and vowel production) showed that all training types led to improvements in perception and production. There was some evidence that improvements were linked to training type: learners in the Perception Training condition improved in vowel identification but not vowel production, while those in the Production Training condition showed only small improvements in performance on perceptual tasks, but greater improvement in production. However, the effects of training modality were complicated by proficiency, with high proficiency learners benefitting more from different types of training regardless of training mode than lower proficiency learners.

How we produce and perceive voice is constrained by laryngeal physiology and biomechanics. Such constraints may present themselves as principal dimensions in the voice outcome space that are shared among speakers. This study attempts to identify such principal dimensions in the voice outcome space and the underlying laryngeal control mechanisms in a three-dimensional computational model of voice production. A large-scale voice simulation was performed with parametric variations in vocal fold geometry and stiffness, glottal gap, vocal tract shape, and subglottal pressure. Principal component analysis was applied to data combining both the physiological control parameters and voice outcome measures. The results showed three dominant dimensions accounting for at least 50% of the total variance. The first two dimensions describe respiratory-laryngeal coordination in controlling the energy balance between low- and high-frequency harmonics in the produced voice, and the third dimension describes control of the fundamental frequency. The dominance of these three dimensions suggests that voice changes along these principal dimensions are likely to be more consistently produced and perceived by most speakers than other voice changes, and thus are more likely to have emerged during evolution and be used to convey important personal information, such as emotion and larynx size.

Advancing age is associated with decreased sensitivity to temporal cues in word segments, particularly when target words follow non-informative carrier sentences or are spectrally degraded (e.g., vocoded to simulate cochlear-implant stimulation). This study investigated whether age, carrier sentences, and spectral degradation interacted to cause undue difficulty in processing speech temporal cues. Younger and older adults with normal hearing performed phonemic categorization tasks on two continua: a Buy/Pie contrast with voice onset time changes for the word-initial stop and a Dish/Ditch contrast with silent interval changes preceding the word-final fricative. Target words were presented in isolation or after non-informative carrier sentences, and were unprocessed or degraded via sinewave vocoding (2, 4, and 8 channels). Older listeners exhibited reduced sensitivity to both temporal cues compared to younger listeners. For the Buy/Pie contrast, age, carrier sentence, and spectral degradation interacted such that the largest age effects were seen for unprocessed words in the carrier sentence condition. This pattern differed from the Dish/Ditch contrast, where reducing spectral resolution exaggerated age effects, but introducing carrier sentences largely left the patterns unchanged. These results suggest that certain temporal cues are particularly susceptible to aging when placed in sentences, likely contributing to the difficulties of older cochlear-implant users in everyday environments.

High-frequency speech information is susceptible to inaccurate perception in even mild to moderate forms of hearing loss. Some hearing aids employ frequency-lowering methods such as nonlinear frequency compression (NFC) to help hearing-impaired individuals access high-frequency speech information in more accessible lower-frequency regions. As such techniques cause significant spectral distortion, tests such as the S-Sh Confusion Test help optimize NFC settings to provide high-frequency audibility with the least distortion. Such tests have been traditionally based on speech contrasts pertinent to English. Here, the effects of NFC processing on fricative perception between English and Mandarin listeners are assessed. Small but significant differences in fricative discrimination were observed between the groups. The study demonstrates possible need for language-specific clinical fitting procedures for NFC.

Speech can be defined as the human ability to communicate through a sequence of vocal sounds. Consequently, speech requires an emitter (the speaker) capable of generating the acoustic signal and a receiver (the listener) able to successfully decode the sounds produced by the emitter (i.e., the acoustic signal). Time plays a central role at both ends of this interaction. On the one hand, speech production requires precise and rapid coordination, typically within the order of milliseconds, of the upper vocal tract articulators (i.e., tongue, jaw, lips, and velum), their composite movements, and the activation of the vocal folds. On the other hand, the generated acoustic signal unfolds in time, carrying information at different timescales. This information must be parsed and integrated by the receiver for the correct transmission of meaning. This chapter describes the temporal patterns that characterize the speech signal and reviews research that explores the neural mechanisms underlying the generation of these patterns and the role they play in speech comprehension.

Speech recognition by both humans and machines frequently fails in non-optimal yet common situations. For example, word recognition error rates for second-language (L2) speech can be high, especially under conditions involving background noise. At the same time, both human and machine speech recognition sometimes shows remarkable robustness against signal- and noise-related degradation. Which acoustic features of speech explain this substantial variation in intelligibility? Current approaches align speech to text to extract a small set of pre-defined spectro-temporal properties from specific sounds in particular words. However, variation in these properties leaves much cross-talker variation in intelligibility unexplained. We examine an alternative approach utilizing a perceptual similarity space acquired using self-supervised learning. This approach encodes distinctions between speech samples without requiring pre-defined acoustic features or speech-to-text alignment. We show that L2 English speech samples are less tightly clustered in the space than L1 samples reflecting variability in English proficiency among L2 talkers. Critically, distances in this similarity space are perceptually meaningful: L1 English listeners have lower recognition accuracy for L2 speakers whose speech is more distant in the space from L1 speech. These results indicate that perceptual similarity may form the basis for an entirely new speech and language analysis approach.

Unilateral vocal cord paralysis is frequently observed in patients who undergo thyroid surgery. This study explored the correlation between acoustic voice analysis (objective measure) and Voice Handicap Index (VHI, a self-assessment tool). One hundred and forty patients who had thyroid surgery with or without postoperative unilateral vocal cord paralysis (PVCP and NPVCP) were included. The patients were evaluated by the VHI and Dysphonia Severity Index (DSI) tools. VHI scores were significantly higher in PVCP patients than in NPVCP patients. Jitter (%) and shimmer (%) were significantly increased, whereas DSI was significantly decreased in PVCP patients. Receiver operating characteristics curve revealed that VHI scores were associated with the diagnosis of PVCP, of which VHI total score yielded an area under the curve (AUC) of 0.81. Among acoustic parameters, DSI was highly associated to PVCP (AUC=0.82, 95%CI=0.75 to 0.89). Moreover, we found a correlation between VHI scores and voice acoustic parameters. Among them, DSI had a moderate correlation with functional and VHI scores, as suggested by an R value of 0.41 and 0.49, respectively. VHI scores and acoustic parameters were associated with the diagnosis of PVCP.

The quality of speech input influences the efficiency of L1 and L2 acquisition. This study examined modifications in infant-directed speech (IDS) and foreigner-directed speech (FDS) in Standard Mandarin-a tonal language-and explored how IDS and FDS features were manifested in disyllabic words and a longer discourse. The study aimed to determine which characteristics of IDS and FDS were enhanced in comparison with adult-directed speech (ADS), and how IDS and FDS differed when measured in a common set of acoustic parameters. For words, it was found that tone-bearing vowel duration, mean and range of fundamental frequency (F0), and the lexical tone contours were enhanced in IDS and FDS relative to ADS, except for the dipping Tone 3 that exhibited an unexpected lowering in FDS, but no modification in IDS when compared with ADS. For the discourse, different aspects of temporal and F0 enhancements were emphasized in IDS and FDS: the mean F0 was higher in IDS whereas the total discourse duration was greater in FDS. These findings add to the growing literature on L1 and L2 speech input characteristics and their role in language acquisition.

Age-related changes in auditory processing may reduce physiological coding of acoustic cues, contributing to older adults\' difficulty perceiving speech in background noise. This study investigated whether older adults differed from young adults in patterns of acoustic cue weighting for categorizing vowels in quiet and in noise. All participants relied primarily on spectral quality to categorize /ɛ/ and /æ/ sounds under both listening conditions. However, relative to young adults, older adults exhibited greater reliance on duration and less reliance on spectral quality. These results suggest that aging alters patterns of perceptual cue weights that may influence speech recognition abilities.

The ability to accurately classify accents and assess accentedness in non-native speakers are challenging tasks due primarily to the complexity and diversity of accent and dialect variations. In this study, embeddings from advanced pretrained language identification (LID) and speaker identification (SID) models are leveraged to improve the accuracy of accent classification and non-native accentedness assessment. Findings demonstrate that employing pretrained LID and SID models effectively encodes accent/dialect information in speech. Furthermore, the LID and SID encoded accent information complement an end-to-end (E2E) accent identification (AID) model trained from scratch. By incorporating all three embeddings, the proposed multi-embedding AID system achieves superior accuracy in AID. Next, leveraging automatic speech recognition (ASR) and AID models is investigated to explore accentedness estimation. The ASR model is an E2E connectionist temporal classification model trained exclusively with American English (en-US) utterances. The ASR error rate and en-US output of the AID model are leveraged as objective accentedness scores. Evaluation results demonstrate a strong correlation between scores estimated by the two models. Additionally, a robust correlation between objective accentedness scores and subjective scores based on human perception is demonstrated, providing evidence for the reliability and validity of using AID-based and ASR-based systems for accentedness assessment in non-native speech. Such advanced systems would benefit accent assessment in language learning as well as speech and speaker assessment for intelligibility, quality, and speaker diarization and speech recognition advancements.