for Computational Linguistics, pages 311-318, Philadelphia, Pennsylvania, USA, July 2002. Association for Computational Linguistics. doi: 10.3115/1073083.1073135. URL https://www.aclweb.org/anthology/P02-1040.
[70] Matt Post. A call for clarity in reporting BLEU scores. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 186-191, Brussels, Belgium, October 2018. Association for Computational Linguistics. doi: 10.18653/v1/W18-6319. URL https://www.aclweb.org/anthology/W18-6319.
[71] Qingkai Fang, Rong Ye, Lei Li, Yang Feng, and Mingxuan Wang. STEMM: Self-learning with speech-text manifold mixup for speech translation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7050-7062, Dublin, Ireland, May 2022. Association for Computational Linguistics. doi: 10.18653/v1/2022.acl-long.486. URL https://aclanthology.org/2022.acl-long.486.
[72] Qingkai Fang and Yang Feng. Understanding and bridging the modality gap for speech translation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15864-15881, Toronto, Canada, July 2023. Association for Computational Linguistics. doi: 10.18653/v1/2023.acl-long.884. URL https://aclanthology.org/2023.acl-long.884.
[73] Yan Zhou, Qingkai Fang, and Yang Feng. CMOT: Cross-modal mixup via optimal transport for speech translation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7873-7887, Toronto, Canada, July 2023. Association for Computational Linguistics. doi: 10.18653/v1/2023.acl-long.436. URL https://aclanthology.org/2023.acl-long.436.
[74] Herman Kamper, Karen Livescu, and Sharon Goldwater. An embedded segmental k-means model for unsupervised segmentation and clustering of speech. In 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pages 719-726, 2017. doi: 10.1109/ASRU.2017.8269008. URL https://www.kamperh.com/papers/kamper+livescu+goldwater_asru2017.pdf.
[75] Herman Kamper, Aren Jansen, and Sharon Goldwater. A segmental framework for fullyunsupervised large-vocabulary speech recognition. Computer Speech & Language, 46:154-174, 2017. ISSN 0885-2308. doi: https://doi.org/10.1016/j.csl.2017.04.008. URL https://www.sciencedirect.com/science/article/pii/S0885230816301905.
[76] Herman Kamper and Benjamin van Niekerk. Towards unsupervised phone and word segmentation using self-supervised vector-quantized neural networks. arXiv e-prints, art. arXiv:2012.07551, December 2020. URL https://ui.adsabs.harvard.edu/abs/2020arXiv201207551K.
[77] Tzeviya Sylvia Fuchs, Yedid Hoshen, and Joseph Keshet. Unsupervised word segmentation using k nearest neighbors. arXiv preprint arXiv:2204.13094, 2022. URL https://arxiv.org/abs/2204.13094.
[78] Mark A. Pitt, Keith Johnson, Elizabeth Hume, Scott Kiesling, and William Raymond. The buckeye corpus of conversational speech: labeling conventions and a test of transcriber reliability. Speech Communication, 45(1):89-95, 2005. ISSN 0167-6393. doi: https://doi.org/10.1016/j.spcom.2004.09.001. URL https://www.sciencedirect.com/science/article/pii/S0167639304000974.
[79] Okko Räsänen, Unto Laine, and Toomas Altosaar. An improved speech segmentation quality measure: the r-value. In 10th Interspeech Conference, Brighton, UK, September 6-10, 2009, 2009. URL https://citeseerx.ist.psu.edu/document?repid=rep1& type=pdf&doi=91ff68c684116aea4de8b407fa79bbf1e05dc3c.
[80] Kris Demuynck and Tom Laureys. A comparison of different approaches to automatic speech segmentation. In Petr Sojka, Ivan Kopeček, and Karel Pala, editors, Text, Speech and Dialogue, pages 277–284, Berlin, Heidelberg, 2002. Springer Berlin Heidelberg. ISBN 978-3-540-46154-8. URL https://link.springer.com/chapter/10.1007/3-540-46154-X_38.