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Examination of the sensitivity of acoustic-phonetic parameters of speech to depression.

, , and . CogInfoCom, page 511-515. IEEE, (2012)

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Automatic cross- and multi-lingual recognition of dysphonia by ensemble classification using deep speaker embedding models., and . Expert Syst. J. Knowl. Eng., (October 2024)Detection Possibilities of Depression and Parkinson's disease Based on the Ratio of Transient Parts of the Speech., , , and . CogInfoCom, page 165-168. IEEE, (2018)Application for Detecting Depression, Parkinson's Disease and Dysphonic Speech., , and . Interspeech, page 956-957. ISCA, (2021)Depression State Assessment: Application for Detection of Depression by Speech., , and . INTERSPEECH, page 966-967. ISCA, (2019)Automatic Assessment of the Degree of Clinical Depression from Speech Using X-Vectors., , , and . ICASSP, page 8502-8506. IEEE, (2022)Examination of the sensitivity of acoustic-phonetic parameters of speech to depression., , and . CogInfoCom, page 511-515. IEEE, (2012)Effect of identical twins on deep speaker embeddings based forensic voice comparison., and . Int. J. Speech Technol., 27 (2): 341-351 (June 2024)Effects of language mismatch in automatic forensic voice comparison using deep learning embeddings., and . CoRR, (2022)Detection of Speech Related Disorders by Pre-trained Embedding Models Extracted Biomarkers., , and . SPECOM, volume 13721 of Lecture Notes in Computer Science, page 279-289. Springer, (2022)Automatikus érzelem-felismerés akusztikai paraméterek alapján. Budapest University of Technology and Economics, Hungary, (2014)