Anlirika: An LSTM–CNN Flow Twister for Spoken Language Identification
Andreas Scherbakov, Liam Whittle, Ritesh Kumar, Siddharth Singh, Matthew Coleman, Ekaterina Vylomova
Abstract
The paper presents Anlirika’s submission to SIGTYP 2021 Shared Task on Robust Spoken Language Identification. The task aims at building a robust system that generalizes well across different domains and speakers. The training data is limited to a single domain only with predominantly single speaker per language while the validation and test data samples are derived from diverse dataset and multiple speakers. We experiment with a neural system comprising a combination of dense, convolutional, and recurrent layers that are designed to perform better generalization and obtain speaker-invariant representations. We demonstrate that the task in its constrained form (without making use of external data or augmentation the train set with samples from the validation set) is still challenging. Our best system trained on the data augmented with validation samples achieves 29.9% accuracy on the test data.- Anthology ID:
- 2021.sigtyp-1.14
- Volume:
- Proceedings of the Third Workshop on Computational Typology and Multilingual NLP
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Ekaterina Vylomova, Elizabeth Salesky, Sabrina Mielke, Gabriella Lapesa, Ritesh Kumar, Harald Hammarström, Ivan Vulić, Anna Korhonen, Roi Reichart, Edoardo Maria Ponti, Ryan Cotterell
- Venue:
- SIGTYP
- SIG:
- SIGTYP
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 145–148
- Language:
- URL:
- https://aclanthology.org/2021.sigtyp-1.14
- DOI:
- 10.18653/v1/2021.sigtyp-1.14
- Cite (ACL):
- Andreas Scherbakov, Liam Whittle, Ritesh Kumar, Siddharth Singh, Matthew Coleman, and Ekaterina Vylomova. 2021. Anlirika: An LSTM–CNN Flow Twister for Spoken Language Identification. In Proceedings of the Third Workshop on Computational Typology and Multilingual NLP, pages 145–148, Online. Association for Computational Linguistics.
- Cite (Informal):
- Anlirika: An LSTM–CNN Flow Twister for Spoken Language Identification (Scherbakov et al., SIGTYP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.sigtyp-1.14.pdf