Charney, Sara

Objectives/Goals: Aspiration causes or aggravates lung diseases. While bedside swallow evaluations are not sensitive/specific, gold standard tests for aspiration are invasive, uncomfortable, expose patients to radiation, and are resource intensive. We propose the development and validation of an AI model that analyzes voice to noninvasively predict aspiration. Methods/Study Population: Retrospectively recorded [i] phonations from 163 unique ENT patients were analyzed for acoustic features including jitter, shimmer, harmonic to noise ratio (HNR), etc. Patients were classified into three groups: aspirators (Penetration-Aspiration Scale, PAS 6–8), probable (PAS 3–5), and non-aspirators (PAS 1–2) based on video fluoroscopic swallow (VFSS) findings. Multivariate analysis evaluated patient demographics, history of head and neck surgery, radiation, neurological illness, obstructive sleep apnea, esophageal disease, body mass index, and vocal cord dysfunction. Supervised machine learning using five folds cross-validated neural additive network modelling (NAM) was performed on the phonations of aspirator versus non-aspirators. The model was then validated using an independent, external database. Results/Anticipated Results: Aspirators were found to have quantifiably worse quality of sound with higher jitter and shimmer but lower harmonics noise ratio. NAM modeling classified aspirators and non-aspirators as distinct groups (aspirator NAM risk score 0.528+0.2478 (mean + std) vs. non-aspirator (control) risk score of 0.252+0.241 (mean + std); p Discussion/Significance of Impact: We report the use of voice as a novel, noninvasive biomarker to detect aspiration risk using machine learning techniques. This tool has the potential to be used for the safe and early detection of aspiration in a variety of clinical settings including intensive care units, wards, outpatient clinics, and remote monitoring.

This study evaluated the feasibility of differentiating conversational and clear speech produced by individuals with muscle tension dysphonia (MTD) using landmark-based analysis of speech (LMBAS). Thirty-four adult speakers with MTD recorded conversational and clear speech, with 27 of them able to produce clear speech. The recordings of these individuals were analyzed with the open-source LMBAS program, SpeechMark®, matlab Toolbox version 1.1.2. The results indicated that glottal landmarks, burst onset landmarks, and the duration between glottal landmarks differentiated conversational speech from clear speech. LMBAS shows potential as an approach for detecting the difference between conversational and clear speech in dysphonic individuals.

The COVID‐19 pandemic has led to many unintended, long‐lasting consequences for society. Preventative practices such as mask wearing, social distancing, and virtual meetings and classrooms to address contagion concerns may negatively affect communication, particularly in the pediatric population, as schools have begun to open this fall. Increasing awareness and creating innovative methods to promote communication and language learning in settings both in person and virtual is paramount. Although more studies are needed to characterize the pandemic’s impact on pediatric speech and language development, clinicians and parents should be cognizant of this phenomenon and proactive in facilitating an optimal communication environment for children.

Objectives/Introduction: Laryngology is an expanding field that has been increasingly incorporated into otolaryngology resident training programs nationwide. The exposure to the field is variable across training programs, despite the fact that laryngological complaints comprise a large proportion of consultations to otolaryngologists. Laryngology education is vital for the care of patients with voice, swallowing, and airway complaints as well as for the appropriate referral of patients to the laryngology team for specialized care. Speech-language pathologists (SLPs) specialized in voice and swallowing disorders are well-trained in the assessment and treatment for these populations. This team recently published a paper regarding the experience of laryngology education in residency. During analysis of the results, an interesting beneficial trend developed regarding the positive impact of exposure to SLPs. This appeared to be distinct and deserved further analysis and discussion. We propose that involving SLPs in resident education may greatly enhance their training in laryngology. Methods: As per our previous paper, a cross sectional, multi-institutional study was designed to assess the exposure of residents to laryngology. Descriptive statistics were obtained for questions involving exposure to SLPs. Fisher’s exact test was used to compare differences between groups. Results: Most respondents (135/151, 89.4%) indicated having SLPs specializing in voice and swallowing disorders in their departments, although only half (77/151, 51.0%) stated that they spent formal time with them during training. Results show that residents with formal training with SLPs were more comfortable interpreting videofluoroscopic swallow studies (VFSS) ( P = .0032). Residents with SLPs in their departments were also more likely to feel confident in terminology to describe different dysphonic voices ( P = .0213). Conclusion: Formal time with SLPs within otolaryngology residency programs varies across the country. Speech-language pathologists are a useful resource for laryngology resident training and should be included in their education.