Who cites «Joint Transition-based Dependency Parsing and Disfluency Detection for Automatic Speech Recognition Texts»

18 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

1. Adversarial Training for Low-Resource Disfluency Correction — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
2. Data-driven Parsing Evaluation for Child-Parent Interactions — our card · 2023
3. Disfluency Detection for Vietnamese — 2022 · Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022)
4. How You Say It Matters: Measuring the Impact of Verbal Disfluency Tags on Automated Dementia Detection — 2022 · Proceedings of the 21st Workshop on Biomedical Language Processing
5. LARD: Large-scale Artificial Disfluency Generation — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
6. Une chaîne de traitements pour la simplification automatique de la parole et sa traduction automatique vers des pictogrammes (Simplification and automatic translation of speech into pictograms ) — 2022 · Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 2 : 24e Rencontres Etudiants Chercheurs en Informatique pour le TAL (RECITAL)
7. The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies — 2021 · Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021)
8. Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency Detection — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
9. Improving Disfluency Detection by Self-Training a Self-Attentive Model — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
10. Planning and Generating Natural and Diverse Disfluent Texts as Augmentation for Disfluency Detection — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
11. Neural Constituency Parsing of Speech Transcripts — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
12. Disfluency Detection using Auto-Correlational Neural Networks — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
13. Er ... well, it matters, right? On the role of data representations in spoken language dependency parsing — 2018 · Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)
14. Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information — 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
15. Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model — 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
16. Enriching ASR Lattices with POS Tags for Dependency Parsing — 2017 · Proceedings of the Workshop on Speech-Centric Natural Language Processing
17. Error-repair Dependency Parsing for Ungrammatical Texts — 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
18. Parsing transcripts of speech — 2017 · Proceedings of the Workshop on Speech-Centric Natural Language Processing