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Daily Activity Recognition with Large-Scaled Real-Life Recording Datasets Based on Deep Neural Network Using Multi-Modal Signals., , , , и . IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 101-A (1): 199-210 (2018)A Statistical Sample-Based Approach to GMM-Based Voice Conversion Using Tied-Covariance Acoustic Models., , , , и . IEICE Trans. Inf. Syst., 99-D (10): 2490-2498 (2016)Structured Adaptive Regularization of Weight Vectors for a Robust Grapheme-to-Phoneme Conversion Model., , , , и . IEICE Trans. Inf. Syst., 97-D (6): 1468-1476 (2014)A Comparative Study of Self-supervised Speech Representation Based Voice Conversion., , , и . CoRR, (2022)Noisy-to-Noisy Voice Conversion Under Variations of Noisy Condition., и . IEEE ACM Trans. Audio Speech Lang. Process., (2023)Singing Fundamental Frequency Contour Generation Using Generalized Command-Response Model and Score-Conditional Variational Autoencoder., , и . MLSP, стр. 1-3. IEEE, (2021)Investigation of Text-to-Speech-based Synthetic Parallel Data for Sequence-to-Sequence Non-Parallel Voice Conversion., , и . APSIPA ASC, стр. 870-877. IEEE, (2021)A Comparative Study of Voice Conversion Models With Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023., , , , и . ASRU, стр. 1-6. IEEE, (2023)The Voicemos Challenge 2023: Zero-Shot Subjective Speech Quality Prediction for Multiple Domains., , , , , и . ASRU, стр. 1-7. IEEE, (2023)ED-CEC: Improving Rare word Recognition Using ASR Postprocessing Based on Error Detection and Context-Aware Error Correction., , и . ASRU, стр. 1-6. IEEE, (2023)