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Non-Autoregressive End-to-End Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding.

, and . SLT, page 390-397. IEEE, (2022)

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Factors in Emotion Recognition With Deep Learning Models Using Speech and Text on Multiple Corpora., , , and . IEEE Signal Process. Lett., (2022)Multiple-hypothesis RNN-T Loss for Unsupervised Fine-tuning and Self-training of Neural Transducer., , and . INTERSPEECH, page 4446-4450. ISCA, (2022)Teacher-Student MixIT for Unsupervised and Semi-Supervised Speech Separation., , , and . Interspeech, page 3495-3499. ISCA, (2021)Time-Domain Speech Extraction with Spatial Information and Multi Speaker Conditioning Mechanism., , , and . ICASSP, page 6084-6088. IEEE, (2021)Non-Autoregressive End-to-End Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding., and . SLT, page 390-397. IEEE, (2022)Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition., , and . CoRR, (2023)Monaural source separation: From anechoic to reverberant environments., , , , , and . CoRR, (2021)Evaluating Large Language Models for Document-grounded Response Generation in Information-Seeking Dialogues., , , and . CoRR, (2023)Monaural Source Separation: From Anechoic To Reverberant Environments., , , , , and . IWAENC, page 1-5. IEEE, (2022)Speaker adaptive training in deep neural networks using speaker dependent bottleneck features.. ICASSP, page 5290-5294. IEEE, (2016)