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Cooking State Recognition based on Acoustic Event Detection.

, , и . CEA@ICMR, стр. 41-44. ACM, (2019)

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Daisuke Yoshida

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Cooking State Recognition based on Acoustic Event Detection., , и . CEA@ICMR, стр. 41-44. ACM, (2019)Voice conversion based on deep neural networks for time-variant linear transformations., , и . APSIPA, стр. 1259-1262. IEEE, (2017)A Revisit to Feature Handling for High-quality Voice Conversion Based on Gaussian Mixture Model., , , и . APSIPA, стр. 816-822. IEEE, (2018)Preliminary Systematic Literature Review of Machine Learning System Development Process., , , , , , , и . CoRR, (2019)A tandem connectionist model using combination of multi-scale spectro-temporal features for acoustic event detection., , , , и . ICASSP, стр. 4293-4296. IEEE, (2012)Experimental investigation on the efficacy of Affine-DTW in the quality of voice conversion., , , и . APSIPA, стр. 119-124. IEEE, (2019)A measure of phonetic similarity to quantify pronunciation variation by using ASR technology., , , , , и . ICPhS, University of Glasgow, (2015)Do learned speech symbols follow Zipf's law?, , , , и . CoRR, (2023)Quality-diversity for Synthesizer Sound Matching., и . J. Inf. Process., (2023)INmfCA Algorithm for Training of Nonparallel Voice Conversion Systems Based on Non-Negative Matrix Factorization., , и . IEICE Trans. Inf. Syst., 105-D (6): 1196-1210 (2022)