OBJECTIVE: To compare and correlate musical performance anxiety (MPA) and vocal self-perception among amateur evangelical singers, focusing on the interaction between anxiety and aspects of performance in this sample.
METHODS: This study employed a cross-sectional and quantitative approach, involving 75 amateur gospel singers from evangelical churches, aged between 18 and 59 years. Data collection included the administration of a sample identification and characterization questionnaire, the Brazilian Portuguese version of the Kenny Music Performance Anxiety Inventory (K-MPAI), and the Singing Voice Handicap Index (S-VHI). The descriptive analysis used absolute and relative frequencies, measures of central tendency, and dispersion (mean and standard deviation [SD]). To compare the vocal self-assessment protocols and performance aspects, the Kruskal-Wallis test was applied. Spearman\'s correlation test was used for correlation analysis. All analyses were conducted with a significance level set at 5% (P < 0.05).
RESULTS: Vocal warm-up and cool-down activities, vocal discomfort after performance, and vocal self-assessment were significantly associated with scores on S-VHI, and the variable \"instruments louder than voices\" was associated with the K-MPAI score. Participants exhibited a mean K-MPAI score of 85.12 points (SD ± 36.6), and the vocal handicap of the sample had a mean score of 45.22 (SD ± 32.3). There was no statistically significant correlation between the protocols.
CONCLUSIONS: Incorporating vocal warm-up and cool-down activities was significantly associated with lower scores on S-VHI. Conversely, those experiencing postperformance vocal discomfort exhibited higher scores on S-VHI. Moreover, the absence of correlation between the assessment protocols suggests that while significant levels of voice handicap were observed, a direct link to MPA cannot be definitively established. Overall, these findings contribute to a nuanced understanding of the multifaceted factors shaping vocal health and performance among amateur evangelical singers, thereby guiding future research and interventions in this field.

Research has indicated unique challenges in audiovisual integration of speech among autistic individuals, although methodological differences have led to divergent findings. We conducted a systematic literature search to identify studies that measured audiovisual speech integration among both autistic and non-autistic individuals. Across the 18 identified studies (combined N = 952), autistic individuals showed impaired audiovisual integration compared to their non-autistic peers (g = 0.69, 95% CI [0.53, 0.85], p <.001). This difference was not found to be influenced by participants\' mean ages, studies\' sample sizes, risk-of-bias scores, or paradigms investigated. However, a subgroup analysis suggested that child studies may show larger between-group differences than adult ones. The prevailing pattern of impaired audiovisual speech integration in autism may have cascading effects on communicative and social behavior. However, small samples and inconsistency in design/analysis translated into considerable heterogeneity in findings and opacity regarding the influence of underlying unisensory and attentional factors. We recommend three key directions for future research: larger samples, more research with adults, and standardization of methodology and analytical approaches.

UNASSIGNED: Respiratory and bulbar dysfunctions (including swallowing, feeding, and speech functions) are key symptoms of spinal muscular atrophy (SMA), especially in its most severe forms. Demonstrating the long-term efficacy of disease-modifying therapies (DMTs) necessitates an understanding of SMA natural history.
UNASSIGNED: This study summarizes published natural history data on respiratory, swallowing, feeding, and speech functions in patients with SMA not receiving DMTs.
UNASSIGNED: Electronic databases (Embase, MEDLINE, and Evidence-Based Medicine Reviews) were searched from database inception to June 27, 2022, for studies reporting data on respiratory and/or bulbar function outcomes in Types 1-3 SMA. Data were extracted into a predefined template and a descriptive summary of these data was provided.
UNASSIGNED: Ninety-one publications were included: 43 reported data on respiratory, swallowing, feeding, and/or speech function outcomes. Data highlighted early loss of respiratory function for patients with Type 1 SMA, with ventilatory support typically required by 12 months of age. Patients with Type 2 or 3 SMA were at risk of losing respiratory function over time, with ventilatory support initiated between the first and fifth decades of life. Swallowing and feeding difficulties, including choking, chewing problems, and aspiration, were reported in patients across the SMA spectrum. Swallowing and feeding difficulties, and a need for non-oral nutritional support, were reported before 1 year of age in Type 1 SMA, and before 10 years of age in Type 2 SMA. Limited data relating to other bulbar functions were collated.
UNASSIGNED: Natural history data demonstrate that untreated patients with SMA experience respiratory and bulbar function deterioration, with a more rapid decline associated with greater disease severity. This study provides a comprehensive repository of natural history data on bulbar function in SMA, and it highlights that consistent assessment of outcomes in this area is necessary to benefit understanding and approval of new treatments.

The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation of machine learning models that classify SARS-CoV-2 infection status or associated respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the REACT-1 survey in England from March 2021 to March 2022, during dominant transmission of the Alpha and Delta SARS-CoV-2 variants and some Omicron variant sublineages. Audio recordings of volitional coughs, exhalations, and speech were collected in the \'Speak up and help beat coronavirus\' digital survey alongside demographic, symptom and self-reported respiratory condition data. Digital survey submissions were linked to SARS-CoV-2 test results. The UK COVID-19 Vocal Audio Dataset represents the largest collection of SARS-CoV-2 PCR-referenced audio recordings to date. PCR results were linked to 70,565 of 72,999 participants and 24,105 of 25,706 positive cases. Respiratory symptoms were reported by 45.6% of participants. This dataset has additional potential uses for bioacoustics research, with 11.3% participants self-reporting asthma, and 27.2% with linked influenza PCR test results.

There is no room for pragmatic expectations about communicative interactions in core cognition. Spelke takes the combinatorial power of the human language faculty to overcome the limits of core cognition. The question is: Why should the combinatorial power of the human language faculty support infants\' pragmatic expectations not merely about speech, but also about nonverbal communicative interactions?

Existing end-to-end speech recognition methods typically employ hybrid decoders based on CTC and Transformer. However, the issue of error accumulation in these hybrid decoders hinders further improvements in accuracy. Additionally, most existing models are built upon Transformer architecture, which tends to be complex and unfriendly to small datasets. Hence, we propose a Nonlinear Regularization Decoding Method for Speech Recognition. Firstly, we introduce the nonlinear Transformer decoder, breaking away from traditional left-to-right or right-to-left decoding orders and enabling associations between any characters, mitigating the limitations of Transformer architectures on small datasets. Secondly, we propose a novel regularization attention module to optimize the attention score matrix, reducing the impact of early errors on later outputs. Finally, we introduce the tiny model to address the challenge of overly large model parameters. The experimental results indicate that our model demonstrates good performance. Compared to the baseline, our model achieves recognition improvements of 0.12%, 0.54%, 0.51%, and 1.2% on the Aishell1, Primewords, Free ST Chinese Corpus, and Common Voice 16.1 datasets of Uyghur, respectively.

Accommodating talker variability is a complex and multi-layered cognitive process. It involves shifting attention to the vocal characteristics of the talker as well as the linguistic content of their speech. Due to an interdependence between voice and phonological processing, multi-talker environments typically incur additional processing costs compared to single-talker environments. A failure or inability to efficiently distribute attention over multiple acoustic cues in the speech signal may have detrimental language learning consequences. Yet, no studies have examined effects of multi-talker processing in populations with atypical perceptual, social and language processing for communication, including autistic people. Employing a classic word-monitoring task, we investigated effects of talker variability in Australian English autistic (n = 24) and non-autistic (n = 28) adults. Listeners responded to target words (e.g., apple, duck, corn) in randomised sequences of words. Half of the sequences were spoken by a single talker and the other half by multiple talkers. Results revealed that autistic participants\' sensitivity scores to accurately-spotted target words did not differ to those of non-autistic participants, regardless of whether they were spoken by a single or multiple talkers. As expected, the non-autistic group showed the well-established processing cost associated with talker variability (e.g., slower response times). Remarkably, autistic listeners\' response times did not differ across single- or multi-talker conditions, indicating they did not show perceptual processing costs when accommodating talker variability. The present findings have implications for theories of autistic perception and speech and language processing.

The present paper examines how English native speakers produce scopally ambiguous sentences and how they make use of gestures and prosody for disambiguation. As a case in point, the participants in the present study produced the English negative quantifiers. They appear in two different positions as (1) The election of no candidate was a surprise (a: \'for those elected, none of them was a surprise\'; b: \'no candidate was elected, and that was a surprise\') and (2) no candidate\'s election was a surprise (a: \'for those elected, none of them was a surprise\'; b: # \'no candidate was elected, and that was a surprise.\' We were able to investigate the gesture production and the prosodic patterns of the positional effects (i.e., a-interpretation is available at two different positions in 1 and 2) and the interpretation effects (i.e., two different interpretations are available in the same position in 1). We discovered that the participants tended to launch more head shakes in the (a) interpretation despites the different positions, but more head nod/beat in the (b) interpretation. While there is not a difference in prosody of no in (a) and (b) interpretation in (1), there are pitch and durational differences between (a) interpretations in (1) and (2). This study points out the abstract similarities across languages such as Catalan and Spanish (Prieto et al. in Lingua 131:136-150, 2013. 10.1016/j.lingua.2013.02.008; Tubau et al. in Linguist Rev 32(1):115-142, 2015. 10.1515/tlr-2014-0016) in the gestural movements, and the meaning is crucial for gesture patterns. We emphasize that gesture patterns disambiguate ambiguous interpretation when prosody cannot do so.

Lip language recognition urgently needs wearable and easy-to-use interfaces for interference-free and high-fidelity lip-reading acquisition and to develop accompanying data-efficient decoder-modeling methods. Existing solutions suffer from unreliable lip reading, are data hungry, and exhibit poor generalization. Here, we propose a wearable lip language decoding technology that enables interference-free and high-fidelity acquisition of lip movements and data-efficient recognition of fluent lip language based on wearable motion capture and continuous lip speech movement reconstruction. The method allows us to artificially generate any wanted continuous speech datasets from a very limited corpus of word samples from users. By using these artificial datasets to train the decoder, we achieve an average accuracy of 92.0% across individuals (n = 7) for actual continuous and fluent lip speech recognition for 93 English sentences, even observing no training burn on users because all training datasets are artificially generated. Our method greatly minimizes users\' training/learning load and presents a data-efficient and easy-to-use paradigm for lip language recognition.

Experiments on visually grounded, definite reference production often manipulate simple visual scenes in the form of grids filled with objects, for example, to test how speakers are affected by the number of objects that are visible. Regarding the latter, it was found that speech onset times increase along with domain size, at least when speakers refer to nonsalient target objects that do not pop out of the visual domain. This finding suggests that even in the case of many distractors, speakers perform object-by-object scans of the visual scene. The current study investigates whether this systematic processing strategy can be explained by the simplified nature of the scenes that were used, and if different strategies can be identified for photo-realistic visual scenes. In doing so, we conducted a preregistered experiment that manipulated domain size and saturation; replicated the measures of speech onset times; and recorded eye movements to measure speakers\' viewing strategies more directly. Using controlled photo-realistic scenes, we find (1) that speech onset times increase linearly as more distractors are present; (2) that larger domains elicit relatively fewer fixation switches back and forth between the target and its distractors, mainly before speech onset; and (3) that speakers fixate the target relatively less often in larger domains, mainly after speech onset. We conclude that careful object-by-object scans remain the dominant strategy in our photo-realistic scenes, to a limited extent combined with low-level saliency mechanisms. A relevant direction for future research would be to employ less controlled photo-realistic stimuli that do allow for interpretation based on context.