Abstract
How well can a state-of-the-art parsing system, developed for the written domain, perform when applied to spontaneous speech data involving different interlocutors? This study addresses this question in a low-resource setting using child-parent conversations from the CHILDES databse. Specifically, we focus on dependency parsing evaluation for utterances of one specific child (18 - 27 months) and her parents. We first present a semi-automatic adaption of the dependency annotation scheme in CHILDES to that of the Universal Dependencies project, an annotation style that is more commonly applied in dependency parsing. Our evaluation demonstrates that an outof-domain biaffine parser trained only on written texts performs well with parent speech. There is, however, much room for improvement on child utterances, particularly at 18 and 21 months, due to cases of omission and repetition that are prevalent in child speech. By contrast, parsers trained or fine-tuned with in-domain spoken data on a much smaller scale can achieve comparable results for parent speech and improve the weak parsing performance for child speech at these earlier ages- Anthology ID:
- 2021.adaptnlp-1.16
- Volume:
- Proceedings of the Second Workshop on Domain Adaptation for NLP
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv, Ukraine
- Editors:
- Eyal Ben-David, Shay Cohen, Ryan McDonald, Barbara Plank, Roi Reichart, Guy Rotman, Yftah Ziser
- Venue:
- AdaptNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 156–165
- Language:
- URL:
- https://aclanthology.org/2021.adaptnlp-1.16
- DOI:
- Cite (ACL):
- Zoey Liu and Emily Prud’hommeaux. 2021. Dependency Parsing Evaluation for Low-resource Spontaneous Speech. In Proceedings of the Second Workshop on Domain Adaptation for NLP, pages 156–165, Kyiv, Ukraine. Association for Computational Linguistics.
- Cite (Informal):
- Dependency Parsing Evaluation for Low-resource Spontaneous Speech (Liu & Prud’hommeaux, AdaptNLP 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.adaptnlp-1.16.pdf
- Code
- zoeyliu18/parsing_speech