BACKGROUND: The escalating global prevalence of obesity has necessitated the exploration of novel diagnostic approaches. Recent scientific inquiries have indicated potential alterations in voice characteristics associated with obesity, suggesting the feasibility of using voice as a noninvasive biomarker for obesity detection.
OBJECTIVE: This study aims to use deep neural networks to predict obesity status through the analysis of short audio recordings, investigating the relationship between vocal characteristics and obesity.
METHODS: A pilot study was conducted with 696 participants, using self-reported BMI to classify individuals into obesity and nonobesity groups. Audio recordings of participants reading a short script were transformed into spectrograms and analyzed using an adapted YOLOv8 model (Ultralytics). The model performance was evaluated using accuracy, recall, precision, and F1-scores.
RESULTS: The adapted YOLOv8 model demonstrated a global accuracy of 0.70 and a macro F1-score of 0.65. It was more effective in identifying nonobesity (F1-score of 0.77) than obesity (F1-score of 0.53). This moderate level of accuracy highlights the potential and challenges in using vocal biomarkers for obesity detection.
CONCLUSIONS: While the study shows promise in the field of voice-based medical diagnostics for obesity, it faces limitations such as reliance on self-reported BMI data and a small, homogenous sample size. These factors, coupled with variability in recording quality, necessitate further research with more robust methodologies and diverse samples to enhance the validity of this novel approach. The findings lay a foundational step for future investigations in using voice as a noninvasive biomarker for obesity detection.

BACKGROUND: The digital era has witnessed an escalating dependence on digital platforms for news and information, coupled with the advent of \"deepfake\" technology. Deepfakes, leveraging deep learning models on extensive data sets of voice recordings and images, pose substantial threats to media authenticity, potentially leading to unethical misuse such as impersonation and the dissemination of false information.
OBJECTIVE: To counteract this challenge, this study aims to introduce the concept of innate biological processes to discern between authentic human voices and cloned voices. We propose that the presence or absence of certain perceptual features, such as pauses in speech, can effectively distinguish between cloned and authentic audio.
METHODS: A total of 49 adult participants representing diverse ethnic backgrounds and accents were recruited. Each participant contributed voice samples for the training of up to 3 distinct voice cloning text-to-speech models and 3 control paragraphs. Subsequently, the cloning models generated synthetic versions of the control paragraphs, resulting in a data set consisting of up to 9 cloned audio samples and 3 control samples per participant. We analyzed the speech pauses caused by biological actions such as respiration, swallowing, and cognitive processes. Five audio features corresponding to speech pause profiles were calculated. Differences between authentic and cloned audio for these features were assessed, and 5 classical machine learning algorithms were implemented using these features to create a prediction model. The generalization capability of the optimal model was evaluated through testing on unseen data, incorporating a model-naive generator, a model-naive paragraph, and model-naive participants.
RESULTS: Cloned audio exhibited significantly increased time between pauses (P<.001), decreased variation in speech segment length (P=.003), increased overall proportion of time speaking (P=.04), and decreased rates of micro- and macropauses in speech (both P=.01). Five machine learning models were implemented using these features, with the AdaBoost model demonstrating the highest performance, achieving a 5-fold cross-validation balanced accuracy of 0.81 (SD 0.05). Other models included support vector machine (balanced accuracy 0.79, SD 0.03), random forest (balanced accuracy 0.78, SD 0.04), logistic regression, and decision tree (balanced accuracies 0.76, SD 0.10 and 0.72, SD 0.06). When evaluating the optimal AdaBoost model, it achieved an overall test accuracy of 0.79 when predicting unseen data.
CONCLUSIONS: The incorporation of perceptual, biological features into machine learning models demonstrates promising results in distinguishing between authentic human voices and cloned audio.

Memory recall and guidance are essential for motor skill acquisition. Like humans learning to speak, male zebra finches learn to sing by first memorizing and then matching their vocalization to the tutor\'s song (TS) during specific developmental periods. Yet, the neuroanatomical substrate supporting auditory-memory-guided sensorimotor learning has remained elusive. Here, using a whole-brain connectome analysis with activity-dependent viral expression, we identified a transient projection into the motor region, HVC, from neuronal ensembles responding to TS in the auditory forebrain, the caudomedial nidopallium (NCM), in juveniles. Virally induced cell death of the juvenile, but not adult, TS-responsive NCM neurons impaired song learning. Moreover, isolation, which delays closure of the sensory, but not the motor, learning period, did not affect the decrease of projections into the HVC from the NCM TS-responsive neurons after the song learning period. Taken together, our results suggest that dynamic axonal pruning may regulate timely auditory-memory-guided vocal learning during development.

OBJECTIVE: This study aimed to provide a comprehensive overview of the systematic reviews that focus on the prevalence of voice disorders (VDs), associated risk factors, and the demographic characteristics of patients with dysphonia. An umbrella review was conducted to identify general research themes in voice literature that might guide future research initiatives and contribute to the classification of VDs as a worldwide health concern.
METHODS: Umbrella review of systematic reviews.
METHODS: Pubmed/Medline and Embase were searched for eligible systematic reviews by two authors independently. Extracted data items included the study publication details, study design, characteristics of the target population, sample size, region/country, and incidence and/or prevalence of the VD(s) of interest.
RESULTS: Forty systematic reviews were included. Sixteen reported a meta-analysis. Great heterogeneity in methods was found. A total of 277,035 patients across the included studies were included with a prevalence ranging from 0%-90%. The countries represented best were the United States and Brazil, with 13 studies each. Aging, occupational voice use, lifestyle choices, and specific comorbidities, such as obesity or hormonal disorders, seem to be associated with an increased prevalence of dysphonia.
CONCLUSIONS: This review underscores the influence of VDs on distinct patient groups and the general population. A variety of modifiable or non-modifiable risk factors, having varied degrees of impact on voice qualities, have been identified. The overall effect of VDs is probably underestimated due to factors, such as sample size, patient selection, underreporting of symptoms, and asymptomatic cases. Employing systematic reviews with consistent methodologies and criteria for diagnosing VDs would enhance the ability to determine the prevalence of VDs and their impact.

OBJECTIVE: To estimate the current prevalence of voice disorders among adults in the United States; to determine the association of individual factors with voice disorders.
METHODS: The 2022 National Health Interview Survey (NHIS) was analyzed to identify adults reporting voice problems in the past 12 months. Demographics were assessed, as well as the duration, severity, and resolution of the voice problem. The relationship between voice problems, gender, lost workdays, and long COVID was investigated. A comparison to the 2012 NHIS was made to determine changes in voice disorder prevalence.
RESULTS: 29.9 million Americans (95%CI[28.3-31.5]) annually report a voice problem, representing 12.2% of the population (95%CI[11.7-12.8%]). Overall, 26.8% and 13.2% reported the severity of their voice problem as moderate or severe, respectively. Only 5.1% (95%CI[4.3-6.0%]) of respondents sought treatment. Most voice problems were resolved within 1 week (53.0%,95%CI[50.9-55.1%]). Females were more likely than males to report a voice problem (14.4% vs. 10.0%,95%CI[13.7-15.1] and [9.3-10.7], respectively). The 17.6 million Americans with long COVID symptoms were more likely to have voice complaints than those without (21.1% vs. 11.6%,95%CI[18.9-23.5%] and [11.1-12.1%], respectively). Lost workdays were not significantly higher for those with voice disorders compared to those without (17.1 vs. 12.9 days,95%CI[12.0-22.1] and [11.0-14.8], respectively).
CONCLUSIONS: Voice problems affect approximately 1 in 8 adults in the U.S. annually, demonstrating an alarming increased prevalence since 2012 using the same survey methodology. Relatively few individuals seek care for their voice problem, despite significant self-reported impact. Further study is required regarding the impact of COVID and changes in voice use patterns on voice disorders.
METHODS: 3 Laryngoscope, 134:3713-3718, 2024.

Negative schizotypal traits potentially can be digitally phenotyped using objective vocal analysis. Prior attempts have shown mixed success in this regard, potentially because acoustic analysis has relied on small, constrained feature sets. We employed machine learning to (a) optimize and cross-validate predictive models of self-reported negative schizotypy using a large acoustic feature set, (b) evaluate model performance as a function of sex and speaking task, (c) understand potential mechanisms underlying negative schizotypal traits by evaluating the key acoustic features within these models, and (d) examine model performance in its convergence with clinical symptoms and cognitive functioning. Accuracy was good (> 80%) and was improved by considering speaking task and sex. However, the features identified as most predictive of negative schizotypal traits were generally not considered critical to their conceptual definitions. Implications for validating and implementing digital phenotyping to understand and quantify negative schizotypy are discussed.

Background: Type 1 Arnold Chiari is a neurological malformation that may be associated with vocal cord paralysis in Children. In most cases, the vocal cord paralysis is related to protrusion of medulla and cerebellum in the foramen magnum, which led to compression on the vagus nerve.Case report: A 12-year-old child underwent suboccipital decompression and C1 laminectomy for a symptomatic type 1 Arnold Chiari malformation. After the surgery, patient reported severe dyspnea, aphonia, and dysphagia. The videolaryngostroboscopy and neurological examinations reported a postoperative bilateral vocal cord abduction paralysis due to bilateral IX and X cranial nerve paralyzes and a bilateral paralysis of the tongue.Discussion: The type 1 Arnold Chiari malformation clinical picture may present with unilateral or bilateral vocal cord paralysis, which may resolve with an adequate management of the disease. However, the neurosurgical decompression and C1 laminectomy may result in bilateral lesion of the IX, X, and XII cranial nerves, and related severe swallowing, aspiration and vocal cord disorders.Conclusion: We reported the first case of bilateral vocal cord abduction paralysis occurring post-neurosurgical decompression and C1 laminectomy in a child with type 1 Arnold Chiari malformation. This case highlights the importance of surgical steps of the procedure in front of the C1 vertebrae where there are IX, X, and XII cranial nerves.

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Following the first descriptions of culture in primates, widespread agreement has developed that the term can be applied to nonhumans as group-specific, socially learned behaviors. While behaviors such as those involving extractive tool use have been researched intensively, we propose that behaviors that are more subtle, less likely to be ecologically constrained, and more likely to be socially shaped, such as cultural forms of communication, provide compelling evidence of culture in nonhuman primates. Additionally, cultural forms of communication can provide novel insights into animal cognition such as the capacity for conformity, conventionalized meanings, arbitrariness in signal forms, and even symbolism. In this paper we focus on evidence from studies conducted on wild great apes. First, we provide a thorough review of what exactly we do know, and by extension don\'t know, about great ape cultural communication. We argue that detailed research on both vocal and gestural communication in wild great apes shows a more nuanced and variable repertoire than once assumed, with increasing support for group-specific variation. Second, we discuss the relevance of great ape cultural communication and its potential for illustrating evolutionary continuity for human-like cultural attributes, namely cumulative culture and symbolism. In sum, a concerted effort to examine cultural forms of communication in great apes could reveal novel evidence for cultural capacities that have thus far been heavily debated in the literature and can simultaneously contribute to an improved understanding of the complex minds of our closest living relatives.

The objective of this manuscript was to review the indications, efficacy, and safety of a 585 nm pulsed dye laser (PDL) in non-malignant laryngeal lesions. Following the PRISMA statement recommendations, three independent authors searched for articles published in PubMed/MEDLINE, the Cochrane Library, Google Scholar, Scielo, and Web of Science. A bias analysis was performed following NICE guidance tools. From the 506 identified publications, 19 observational studies met the inclusion criteria. The PDL improves vocal quality objectively and subjectively in vascular lesions (p < 0.005) and improves vocal quality in patients with dysplasia/leukoplasia without changing the natural history of the disease compared to other treatments. Reinke\'s edema and granulomas require an average of 1.5 PDL sessions for resolution. Treatment of recurrent respiratory papillomatosis requires multiple sessions, with complete remission achieved in 50-70% of patients. Regardless of the lesion, the tolerance of the procedure under local anesthesia is exceptional (84-97%), and the results in terms of regression and vocal quality are promising. The complication rate is minimal, and the procedure does not interfere with other treatment alternatives. There is no consensus on laser settings. The lack of consistent use in evaluating vocal outcomes, whether objective or subjective, prevents the comparability between studies. The 585 nm pulsed dye laser appears to be an effective and safe therapeutic option in patients with non-malignant laryngeal pathology. Future controlled studies are needed to compare the 585 nm pulsed dye laser with other lasers or cold instrument procedures.