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Convolutional neural network bottleneck features for bi-directional generalized variable parameter HMMs., , и . ICIA, стр. 1126-1131. IEEE, (2016)A Multi-level Acoustic Feature Extraction Framework for Transformer Based End-to-End Speech Recognition., , , , и . INTERSPEECH, стр. 3173-3177. ISCA, (2022)Multimodal learning using 3D audio-visual data for audio-visual speech recognition., , и . IALP, стр. 40-43. IEEE, (2017)Exploiting Cross-Domain Visual Feature Generation for Disordered Speech Recognition., , , , , , , , и . INTERSPEECH, стр. 711-715. ISCA, (2020)A multi-channel/multi-speaker interactive 3D audio-visual speech corpus in Mandarin., , , и . ISCSLP, стр. 1-5. IEEE, (2016)Automatic Complexity Control of Generalized Variable Parameter HMMs for Noise Robust Speech Recognition., , и . IEEE ACM Trans. Audio Speech Lang. Process., 23 (1): 102-114 (2015)An Investigation of Magnitude-Based and Phase-Based Features for Large-Scale Speaker Identification., , , , и . IALP, стр. 173-177. IEEE, (2022)Generalized variable parameter HMMs based acoustic-to-articulatory inversion., , , и . INTERSPEECH, стр. 279-283. ISCA, (2015)Semi-supervised Cross-domain Visual Feature Learning for Audio-Visual Broadcast Speech Transcription., , и . INTERSPEECH, стр. 3509-3513. ISCA, (2018)A New Method for Predicting Severity Level of Dysarthric Speech Based on Joint Feature-Sample Selection using Audio-Visual Data., , , , , , , и . IALP, стр. 190-195. IEEE, (2022)