Abstract
This paper examines the effectiveness of different feature representations of audio data in accurately classifying discourse meaning in Spanish. The task involves determining whether an utterance is a declarative sentence, an interrogative, an imperative, etc. We explore how pitch contour can be represented for a discourse-meaning classification task, employing three different audio features: MFCCs, Mel-scale spectrograms, and chromagrams. We also determine if utilizing means is more effective in representing the speech signal, given the large number of coefficients produced during the feature extraction process. Finally, we evaluate whether these feature representation techniques are sensitive to speaker information. Our results show that a recurrent neural network architecture in conjunction with all three feature sets yields the best results for the task.- Anthology ID:
- 2023.ranlp-1.15
- Volume:
- Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
- Month:
- September
- Year:
- 2023
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd., Shoumen, Bulgaria
- Note:
- Pages:
- 132–142
- Language:
- URL:
- https://aclanthology.org/2023.ranlp-1.15
- DOI:
- Cite (ACL):
- Santiago Arróniz and Sandra Kübler. 2023. Was That a Question? Automatic Classification of Discourse Meaning in Spanish. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 132–142, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
- Cite (Informal):
- Was That a Question? Automatic Classification of Discourse Meaning in Spanish (Arróniz & Kübler, RANLP 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2023.ranlp-1.15.pdf