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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)Are word boundaries useful for unsupervised language learning?, , , , , and . CoRR, (2022)Stop: A Dataset for Spoken Task Oriented Semantic Parsing., , , , , , , , , and 5 other author(s). SLT, page 991-998. IEEE, (2022)Evaluating the Reliability of Acoustic Speech Embeddings., , , and . INTERSPEECH, page 4621-4625. ISCA, (2020)Fine-Tuning Strategies for Faster Inference Using Speech Self-Supervised Models: A Comparative Study., , , , and . ICASSP Workshops, page 1-5. IEEE, (2023)Big model only for hard audios: Sample dependent Whisper model selection for efficient inferences., , and . CoRR, (2023)DP-Parse: Finding Word Boundaries from Raw Speech with an Instance Lexicon., , , , , , , and . CoRR, (2022)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)Do Coarser Units Benefit Cluster Prediction-Based Speech Pre-Training?, , , , , , , , and . ICASSP, page 1-5. IEEE, (2023)