BACKGROUND: Digital speech assessment has potential relevance in the earliest, preclinical stages of Alzheimer\'s disease (AD). We evaluated the feasibility, test-retest reliability, and association with AD-related amyloid-beta (Aβ) pathology of speech acoustics measured over multiple assessments in a remote setting.
METHODS: Fifty cognitively unimpaired adults (Age 68 ± 6.2 years, 58% female, 46% Aβ-positive) completed remote, tablet-based speech assessments (i.e., picture description, journal-prompt storytelling, verbal fluency tasks) for five days. The testing paradigm was repeated after 2-3 weeks. Acoustic speech features were automatically extracted from the voice recordings, and mean scores were calculated over the 5-day period. We assessed feasibility by adherence rates and usability ratings on the System Usability Scale (SUS) questionnaire. Test-retest reliability was examined with intraclass correlation coefficients (ICCs). We investigated the associations between acoustic features and Aβ-pathology, using linear regression models, adjusted for age, sex and education.
RESULTS: The speech assessment was feasible, indicated by 91.6% adherence and usability scores of 86.0 ± 9.9. High reliability (ICC ≥ 0.75) was found across averaged speech samples. Aβ-positive individuals displayed a higher pause-to-word ratio in picture description (B = -0.05, p = 0.040) and journal-prompt storytelling (B = -0.07, p = 0.032) than Aβ-negative individuals, although this effect lost significance after correction for multiple testing.
CONCLUSIONS: Our findings support the feasibility and reliability of multi-day remote assessment of speech acoustics in cognitively unimpaired individuals with and without Aβ-pathology, which lays the foundation for the use of speech biomarkers in the context of early AD.

A computational neuromuscular control system that generates lung pressure and three intrinsic laryngeal muscle activations (cricothyroid, thyroarytenoid, and lateral cricoarytenoid) to control the vocal source was developed. In the current study, LeTalker, a biophysical computational model of the vocal system was used as the physical plant. In the LeTalker, a three-mass vocal fold model was used to simulate self-sustained vocal fold oscillation. A constant/ǝ/vowel was used for the vocal tract shape. The trachea was modeled after MRI measurements. The neuromuscular control system generates control parameters to achieve four acoustic targets (fundamental frequency, sound pressure level, normalized spectral centroid, and signal-to-noise ratio) and four somatosensory targets (vocal fold length, and longitudinal fiber stress in the three vocal fold layers). The deep-learning-based control system comprises one acoustic feedforward controller and two feedback (acoustic and somatosensory) controllers. Fifty thousand steady speech signals were generated using the LeTalker for training the control system. The results demonstrated that the control system was able to generate the lung pressure and the three muscle activations such that the four acoustic and four somatosensory targets were reached with high accuracy. After training, the motor command corrections from the feedback controllers were minimal compared to the feedforward controller except for thyroarytenoid muscle activation.

Abnormal speech prosody has been widely reported in individuals with autism. Many studies on children and adults with autism spectrum disorder speaking a non-tonal language showed deficits in using prosodic cues to mark focus. However, focus marking by autistic children speaking a tonal language is rarely examined. Cantonese-speaking children may face additional difficulties because tonal languages require them to use prosodic cues to achieve multiple functions simultaneously such as lexical contrasting and focus marking. This study bridges this research gap by acoustically evaluating the use of Cantonese speech prosody to mark information structure by Cantonese-speaking children with and without autism spectrum disorder. We designed speech production tasks to elicit natural broad and narrow focus production among these children in sentences with different tone combinations. Acoustic correlates of prosodic focus marking like f0, duration and intensity of each syllable were analyzed to examine the effect of participant group, focus condition and lexical tones. Our results showed differences in focus marking patterns between Cantonese-speaking children with and without autism spectrum disorder. The autistic children not only showed insufficient on-focus expansion in terms of f0 range and duration when marking focus, but also produced less distinctive tone shapes in general. There was no evidence that the prosodic complexity (i.e. sentences with single tones or combinations of tones) significantly affected focus marking in these autistic children and their typically-developing (TD) peers.

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.

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.

This study aims to investigate the effect of detoxification on acoustic features of Mandarin speech. Speech recordings were collected from 66 male abstinent heroin users with different durations of drug detoxification, specifically early abstinent users with a detoxification duration of less than 2 years, sustained abstinent users with 2 years of detoxification, and long-term abstinent users with a detoxification duration of more than 2 years. The results of the acoustic analyses showed that early abstinent users exhibited lower loudness, relative energies of F1, F2, and F3, higher H1-A3, and fewer loudness peaks per second, as well as a longer average duration of unvoiced segments, compared to the sustained and long-term abstinent users. The findings suggest that detoxification may lead to a rehabilitation process in the speech production of abstinent heroin users (e.g., less vocal hoarseness). This study not only provides valuable insights into the effect of detoxification on speech production but also provides a theoretical basis for the speech rehabilitation and detoxification treatment of heroin users.

UNASSIGNED: Although different factors and voice measures have been associated with phonotraumatic vocal hyperfunction (PVH), it is unclear what percentage of individuals with PVH exhibit such differences during their daily lives. This study used a machine learning approach to quantify the consistency with which PVH manifests according to ambulatory voice measures. Analyses included acoustic parameters of phonation as well as temporal aspects of phonation and rest, with the goal of determining optimally consistent signatures of PVH.
UNASSIGNED: Ambulatory neck-surface acceleration signals were recorded over 1 week from 116 female participants diagnosed with PVH and age-, sex-, and occupation-matched vocally healthy controls. The consistency of the manifestation of PVH was defined as the percentage of participants in each group that exhibited an atypical signature based on a target voice measure. Evaluation of each machine learning model used nested 10-fold cross-validation to improve the generalizability of findings. In Experiment 1, we trained separate logistic regression models based on the distributional characteristics of 14 voice measures and durations of voicing and resting segments. In Experiments 2 and 3, features of voicing and resting duration augmented the existing distributional characteristics to examine whether more consistent signatures would result.
UNASSIGNED: Experiment 1 showed that the difference in the magnitude of the first two harmonics (H1-H2) exhibited the most consistent signature (69.4% of participants with PVH and 20.4% of controls had an atypical H1-H2 signature), followed by spectral tilt over eight harmonics (73.6% participants with PVH and 32.1% of controls had an atypical spectral tilt signature) and estimated sound pressure level (SPL; 66.9% participants with PVH and 27.6% of controls had an atypical SPL signature). Additionally, 77.6% of participants with PVH had atypical resting duration, with 68.9% exhibiting atypical voicing duration. Experiments 2 and 3 showed that augmenting the best-performing voice measures with univariate features of voicing or resting durations yielded only incremental improvement in the classifier\'s performance.
UNASSIGNED: Females with PVH were more likely to use more abrupt vocal fold closure (lower H1-H2), phonate louder (higher SPL), and take shorter vocal rests. They were also less likely to use higher fundamental frequency during their daily activities. The difference in the voicing duration signature between participants with PVH and controls had a large effect size, providing strong empirical evidence regarding the role of voice use in the development of PVH.

Cochlear implant users experience difficulties controlling their vocalizations compared to normal hearing peers. However, less is known about their voice quality. The primary aim of the present study was to determine if cochlear implant users\' voice quality would be categorized as dysphonic by the Acoustic Voice Quality Index (AVQI) and smoothed cepstral peak prominence (CPPS). A secondary aim was to determine if vocal quality is further impacted when using bilateral implants compared to using only one implant. The final aim was to determine how residual hearing impacts voice quality. Twenty-seven cochlear implant users participated in the present study and were recorded while sustaining a vowel and while reading a standardized passage. These recordings were analyzed to calculate the AVQI and CPPS. The results indicate that CI users\' voice quality was detrimentally affected by using their CI, raising to the level of a dysphonic voice. Specifically, when using their CI, mean AVQI scores were 4.0 and mean CPPS values were 11.4 dB, which indicates dysphonia. There were no significant differences in voice quality when comparing participants with bilateral implants to those with one implant. Finally, for participants with residual hearing, as hearing thresholds worsened, the likelihood of a dysphonic voice decreased.

Speech is produced by a nonlinear, dynamical Vocal Tract (VT) system, and is transmitted through multiple (air, bone and skin conduction) modes, as captured by the air, bone and throat microphones respectively. Speaker specific characteristics that capture this nonlinearity are rarely used as stand-alone features for speaker modeling, and at best have been used in tandem with well known linear spectral features to produce tangible results. This paper proposes Recurrent Plot (RP) embeddings as stand-alone, non-linear speaker-discriminating features. Two datasets, the continuous multimodal TIMIT speech corpus and the consonant-vowel unimodal syllable dataset, are used in this study for conducting closed-set speaker identification experiments. Experiments with unimodal speaker recognition systems show that RP embeddings capture the nonlinear dynamics of the VT system which are unique to every speaker, in all the modes of speech. The Air (A), Bone (B) and Throat (T) microphone systems, trained purely on RP embeddings perform with an accuracy of 95.81%, 98.18% and 99.74%, respectively. Experiments using the joint feature space of combined RP embeddings for bimodal (A-T, A-B, B-T) and trimodal (A-B-T) systems show that the best trimodal system (99.84% accuracy) performs on par with trimodal systems using spectrogram (99.45%) and MFCC (99.98%). The 98.84% performance of the B-T bimodal system shows the efficacy of a speaker recognition system based entirely on alternate (bone and throat) speech, in the absence of the standard (air) speech. The results underscore the significance of the RP embedding, as a nonlinear feature representation of the dynamical VT system that can act independently for speaker recognition. It is envisaged that speech recognition too will benefit from this nonlinear feature.