Abstract
Code-mixing has become mainstream in the modern, globalised world and affects low-resource languages, such as Latvian, in particular. Solutions to developing an automatic speech recognition system (ASR) for code-mixed speech often rely on specially created audio-text corpora, which are expensive and time-consuming to create. In this work, we attempt to tackle code-mixed Latvian-English speech recognition by improving the language model (LM) of a hybrid ASR system. We make a distinction between inflected transliterations and phonetic transcriptions as two different foreign word types. We propose an inflected transliteration model and a phonetic transcription model for the automatic generation of said word types. We then leverage a large human-translated English-Latvian parallel text corpus to generate synthetic code-mixed Latvian sentences by substituting in generated foreign words. Using the newly created augmented corpora, we train a new LM and combine it with our existing Latvian acoustic model (AM). For evaluation, we create a specialised foreign word test set on which our methods yield up to 15% relative CER improvement. We then further validate these results in a human evaluation campaign.- Anthology ID:
- 2024.lrec-main.308
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 3469–3479
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.308
- DOI:
- Cite (ACL):
- Martins Kronis, Askars Salimbajevs, and Mārcis Pinnis. 2024. Code-Mixed Text Augmentation for Latvian ASR. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 3469–3479, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Code-Mixed Text Augmentation for Latvian ASR (Kronis et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.308.pdf