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SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities.

, , , , , , , , , , , , , , , , and . ACL (1), page 8479-8492. Association for Computational Linguistics, (2022)

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TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech., , and . CoRR, (2020)Don't Speak Too Fast: The Impact of Data Bias on Self-Supervised Speech Models., , , and . ICASSP, page 3258-3262. IEEE, (2022)TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech., , and . IEEE ACM Trans. Audio Speech Lang. Process., (2021)Don't speak too fast: The impact of data bias on self-supervised speech models., , , and . CoRR, (2021)SUPERB: Speech Processing Universal PERformance Benchmark., , , , , , , , , and 10 other author(s). Interspeech, page 1194-1198. ISCA, (2021)Understanding Self-Attention of Self-Supervised Audio Transformers., , and . INTERSPEECH, page 3785-3789. ISCA, (2020)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)QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition., , , , , and . CoRR, (2022)Parallel Synthesis for Autoregressive Speech Generation., , , and . CoRR, (2022)Unsupervised End-to-End Learning of Discrete Linguistic Units for Voice Conversion., , and . INTERSPEECH, page 1108-1112. ISCA, (2019)