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Modal and Nonmodal Voice Quality Classification Using Acoustic and Electroglottographic Features.

, , , and . IEEE ACM Trans. Audio Speech Lang. Process., 25 (12): 2281-2291 (2017)

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Noise and Channel Normalized Cepstral Features for Far-speech Recognition., , and . SPECOM, volume 8113 of Lecture Notes in Computer Science, page 241-248. Springer, (2013)Toward Sleep Study Automation: Detection Evaluation of Respiratory-Related Events., , , and . IEEE J. Biomed. Health Informatics, 26 (7): 3418-3426 (2022)F0 Variability Measures Based on Glottal Closure Instants., , and . INTERSPEECH, page 1986-1989. ISCA, (2019)Spectrally selective dithering for distorted speech recognition., , and . INTERSPEECH, page 2858-2861. ISCA, (2015)Small and Large Vocabulary Speech Recognition of MP3 Data under Real-Word Conditions: Experimental Study., and . ICETE (Selected Papers), volume 314 of Communications in Computer and Information Science, page 409-419. Springer, (2011)Dithering techniques in automatic recognition of speech corrupted by MP3 compression: Analysis, solutions and experiments., , , and . Speech Commun., (2017)The Althingi ASR System., , , , , and . INTERSPEECH, page 3013-3017. ISCA, (2019)Vocal tract and voice source features for monitoring cognitive workload., , , , and . CogInfoCom, page 97-102. IEEE, (2016)Modal and Nonmodal Voice Quality Classification Using Acoustic and Electroglottographic Features., , , and . IEEE ACM Trans. Audio Speech Lang. Process., 25 (12): 2281-2291 (2017)Advanced acoustic modelling techniques in MP3 speech recognition., , and . EURASIP J. Audio Speech Music. Process., (2015)