Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866909226855563264 |
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| author | Pupier, Adrien Coavoux, Maximin Goulian, Jérôme Lecouteux, Benjamin |
| author_facet | Pupier, Adrien Coavoux, Maximin Goulian, Jérôme Lecouteux, Benjamin |
| contents | Direct dependency parsing of the speech signal -- as opposed to parsing speech transcriptions -- has recently been proposed as a task (Pupier et al. 2022), as a way of incorporating prosodic information in the parsing system and bypassing the limitations of a pipeline approach that would consist of using first an Automatic Speech Recognition (ASR) system and then a syntactic parser. In this article, we report on a set of experiments aiming at assessing the performance of two parsing paradigms (graph-based parsing and sequence labeling based parsing) on speech parsing. We perform this evaluation on a large treebank of spoken French, featuring realistic spontaneous conversations. Our findings show that (i) the graph based approach obtain better results across the board (ii) parsing directly from speech outperforms a pipeline approach, despite having 30% fewer parameters. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2406_12621 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech Pupier, Adrien Coavoux, Maximin Goulian, Jérôme Lecouteux, Benjamin Computation and Language Direct dependency parsing of the speech signal -- as opposed to parsing speech transcriptions -- has recently been proposed as a task (Pupier et al. 2022), as a way of incorporating prosodic information in the parsing system and bypassing the limitations of a pipeline approach that would consist of using first an Automatic Speech Recognition (ASR) system and then a syntactic parser. In this article, we report on a set of experiments aiming at assessing the performance of two parsing paradigms (graph-based parsing and sequence labeling based parsing) on speech parsing. We perform this evaluation on a large treebank of spoken French, featuring realistic spontaneous conversations. Our findings show that (i) the graph based approach obtain better results across the board (ii) parsing directly from speech outperforms a pipeline approach, despite having 30% fewer parameters. |
| title | Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2406.12621 |