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The Zero Resource Speech Challenge 2020: Discovering Discrete Subword and Word Units.

, , , , , , , , and . INTERSPEECH, page 4831-4835. ISCA, (2020)

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XLS-R fine-tuning on noisy word boundaries for unsupervised speech segmentation into words., , , and . EMNLP (Findings), page 12103-12112. Association for Computational Linguistics, (2023)Stop: A Dataset for Spoken Task Oriented Semantic Parsing., , , , , , , , , and 5 other author(s). SLT, page 991-998. IEEE, (2022)Are word boundaries useful for unsupervised language learning?, , , , , and . CoRR, (2022)Evaluating the Reliability of Acoustic Speech Embeddings., , , and . INTERSPEECH, page 4621-4625. ISCA, (2020)DP-Parse: Finding Word Boundaries from Raw Speech with an Instance Lexicon., , , , , , , and . CoRR, (2022)Big model only for hard audios: Sample dependent Whisper model selection for efficient inferences., , and . CoRR, (2023)Fine-Tuning Strategies for Faster Inference Using Speech Self-Supervised Models: A Comparative Study., , , , and . ICASSP Workshops, page 1-5. IEEE, (2023)SpiRit-LM: Interleaved Spoken and Written Language Model., , , , , , , , , and 4 other author(s). CoRR, (2024)STOP: A dataset for Spoken Task Oriented Semantic Parsing., , , , , , , , , and 5 other author(s). CoRR, (2022)The Zero Resource Speech Challenge 2019: TTS Without T., , , , , , , , , and 3 other author(s). INTERSPEECH, page 1088-1092. ISCA, (2019)