Ishikawa, Keiko

Abstract Objective Effective communication with humans and automated voice assistants (AVA) is essential for full participation in modern life. Because AVA relies on intelligible speech, individuals with speech impairments, such as those treated for oral cavity cancer (OCC), may face barriers when interacting with AVA. We assessed self‐reported communication difficulty in patients treated for OCC related to AVA and humans. Study Design Prospective cross‐sectional cohort study. Setting Out‐patient clinics in two tertiary care centers. Methods This study was conducted between July 2024 and March 2025 and included adults (≥18 years) diagnosed with and surgically treated for OCC (experimental group) and those without speech impairments (controls). Participants completed the Speech Communication Experience Survey (SCES), which assessed perceived intelligibility when communicating with familiar partners, strangers, and AVA; and, as reported elsewhere, the Speech Handicap Index (SHI). Results In total, 159 participants were included (69 OCC, 90 controls). OCC participants were more likely to report that familiar partners, strangers, and AVA “almost always” or “always” had difficulty understanding their speech ( P < .05). Free flap reconstruction and maxillectomy were associated with greater reported communication difficulty. AVA usage frequency and overall opinions toward AVA did not significantly differ between groups. Conclusion Patients treated for OCC report significantly greater difficulty being understood by both AVA and human listeners compared to controls. These perceptions may inform peri‐operative counseling and guide the development of more inclusive AVA technologies capable of accommodating diverse speakers. Level of Evidence : 3.

ABSTRACT Background Individuals with oral cavity cancer (OCC) have negatively impacted functional status and quality of life. Little is known regarding patients' perspectives of their speech impairments. This study compared self‐reported speech function between patients surgically treated for OCC and healthy controls using the Speech Handicap Index (SHI) and identified factors associated with worse scores. Methods This is a multiinstitutional cross‐sectional study of OCC patients and healthy controls recruited between July 2024 and March 2025. Participants completed the SHI and self‐reported speech quality. Demographics, tumor, and treatment details were abstracted from the electronic health record for OCC. Group differences were assessed with t ‐tests, χ 2 , and Fisher's exact tests. Results Among 69 OCC and 90 controls, OCC patients had significantly higher mean SHI scores (50.2 vs. 34.7, p < 0.01) and were less likely to rate their speech as “good” or “excellent” (47.8% vs. 85.6%, p < 0.01). Both speech and psychosocial domain scores were significantly worse among OCC. Free flap reconstruction was associated with worse scores (29.6 vs. 15.5, p = 0.02) and worse self‐rated speech quality. Conclusions Patients with surgically treated oral cavity cancer have significantly impaired self‐perceived speech and psychosocial functioning compared with healthy individuals. Greater deficits were observed in patients who required free flap reconstruction. Despite the functional deficit, nearly half of OCC patients reported satisfaction with their speech quality. These findings highlight the importance of using validated measures for speech function and support the need for early, multidisciplinary rehabilitation including speech therapy in this population, particularly for those undergoing free flap reconstruction.

Abstract Introduction Acoustic analysis of speech has discriminated decompensated acute heart failure (HF). Speech rate (SR) and cepstral peak prominence (CPP) variation are among features previously evaluated. However, the association between SR and CPP and chronic stable HF with and without pulmonary hypertension (PH) as well as PH alone have not been previously studied. Methods Patients evaluated for HF and/or PH in the outpatient setting recorded a standardized text read out loud from which a sentence was extracted and analysed to extract pre-specified acoustic features including SR and CPP calculated for voiced speech (CPP-V) and in all speech (CPP-All). Patients were grouped depending on the presence or absence of disease (HF and/or PH) and symptoms. Linear regression models were fitted to determine the association between each acoustic feature and disease status. Results In total, 2153 patients were included: age 65.32 ± 17.18 years; male n = 1246 (57.9%); 879 had HF (40.8%), 542 had PH (25.2%) and 777 had no disease and no symptoms (36.1%). After adjustment for age and sex, SR was significantly lower in patients with PH only [estimated coefficient, 95% confidence interval (CI): −0.14, −0.21 to −0.06, P = 0.0006], HF only (−0.11, −0.17 to −0.05, P = 0.0002) and HF with PH (−0.17, −0.24 to −0.10, P &lt; 0.0001) compared with no disease. CPP-V differed in patients with PH only (0.37, 0.16–0.57, P = 0.0004) and CPP-All differed significantly compared with patients without disease (0.23, 0.08–0.38, P = 0.0025). Conclusions SR is significantly slower in patients with HF alone, PH alone and HF and PH combined compared with patients without disease. CPP also differs significantly in patients with PH compared with controls. These findings suggest that acoustic analysis may be useful in discriminating chronic stable HF and PH, offering promise for the development of non-invasive screening methods for HF and PH.

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.

Pietrowicz et al. (2022) demonstrated feasibility of detecting potential speech-based biomarkers to identify gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE); however, speech samples were obtained using research-grade recording equipment (TASCAM DR-40X with AKG C555L microphone). The use of more readily available equipment such as the Apple iPad with a native microphone could simplify data collection and allow access to a broader range of participants. Therefore, this study compared the research-grade recordings to iPad recordings for feasibility of detecting GERD and BE. One-hundred-fifty adults, clinically classified as GERD negative or GERD positive with or without BE, recorded a paragraph (The Rainbow Passage) simultaneously on both a TASCAM and iPad. Both data sets were analyzed manually for Alpha Ratio and Cepstral Peak Prominence (CPP) with Praat. Initial results show significantly higher alpha ratio and lower CPP in iPad recordings, indicating greater noise energy in the high-frequency range. Additionally, the capability of machine and deep learning model types to discern across GERD negative, GERD positive, BE, and normal voices were compared. Detection across these conditions and comparison of acoustic findings were explored to determine usefulness of the less controlled option of recording using an iPad with its internal microphone.

This study explores the feasibility of detecting gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE) using acoustic features extracted from speech recordings. GERD is a common condition affecting up to 27.8% of adults in the US. Chronic GERD is associated with BE, the precursor to esophageal adenocarcinoma. An automatic screening tool for GERD would improve clinical outcomes by improving early detection. Biomarkers based on acoustic features of speech may hold promise as hoarseness often co-occurs with GERD. The study cohort consisted of 49 adults with and 63 without GERD based on esophagogastroduodenoscopy or ambulatory pH studies. Speech, including sustained vowels, sentences, and reading, was systematically recorded. Voice quality was validated through auditory-perceptualratings with three speech-language pathologists. Automated, cross-validated, search across multiple machine and deep learning model types was performed using the recorded speech. Detection of condition presence and severity are explored, and model performance is reported, along with an assessment of the ability of acoustic features to discern across conditions.