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Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering.

, , and . INTERSPEECH, page 2983-2987. ISCA, (2023)

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Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering., , and . CoRR, (2023)Mandarin-English Code-switching Speech Recognition with Self-supervised Speech Representation Models., , , and . CoRR, (2021)DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning., , , , and . CoRR, (2023)End-to-end Whispered Speech Recognition with Frequency-weighted Approaches and Layer-wise Transfer Learning., , , and . CoRR, (2020)M-SpeechCLIP: Leveraging Large-Scale, Pre-Trained Models for Multilingual Speech to Image Retrieval., , , , , and . CoRR, (2022)Non-autoregressive Mandarin-English Code-switching Speech Recognition with Pinyin Mask-CTC and Word Embedding Regularization., , , and . CoRR, (2021)CoLLD: Contrastive Layer-to-layer Distillation for Compressing Multilingual Pre-trained Speech Encoders., , , , and . CoRR, (2023)M-SpeechCLIP: Leveraging Large-Scale, Pre-Trained Models for Multilingual Speech to Image Retrieval., , , , , and . ICASSP, page 1-5. IEEE, (2023)Distilhubert: Speech Representation Learning by Layer-Wise Distillation of Hidden-Unit Bert., , and . ICASSP, page 7087-7091. IEEE, (2022)SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities., , , , , , , , , and 7 other author(s). ACL (1), page 8479-8492. Association for Computational Linguistics, (2022)