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Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity.

, , , , and . IEEE Trans. Biomed. Eng., 51 (2): 325-332 (2004)

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Learning from Few Subjects with Large Amounts of Voice Monitoring Data., , , , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 704-720. PMLR, (2019)Development of sound source components for a new electrolarynx speech prosthesis., , , and . ICASSP, page 2347-2350. IEEE Computer Society, (1999)Subglottal Impedance-Based Inverse Filtering of Voiced Sounds Using Neck Surface Acceleration., , , , and . IEEE Trans. Speech Audio Process., 21 (9): 1929-1939 (2013)Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Sample Size Estimation and Reducing Overfitting., , and . CoRR, (2023)Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity., , , , and . IEEE Trans. Biomed. Eng., 51 (2): 325-332 (2004)Discriminating speakers with vocal nodules using aerodynamic and acoustic features., , and . ICASSP, page 77-80. IEEE Computer Society, (1999)Relationships Between Vocal Function Measures Derived from an Acoustic Microphone and a Subglottal Neck-Surface Accelerometer., , and . IEEE ACM Trans. Audio Speech Lang. Process., 24 (4): 659-668 (2016)Triangular body-cover model of the vocal folds with coordinated activation of five intrinsic laryngeal muscles with applications to vocal hyperfunction., , , , and . CoRR, (2021)Duration of ambulatory monitoring needed to accurately estimate voice use., , , , , , and . INTERSPEECH, page 1335-1338. ISCA, (2012)Smartphone-based detection of voice disorders by long-term monitoring of neck acceleration features., , , , , and . BSN, page 1-6. IEEE, (2013)