Abstract
We present a preprocessed, ready-to-use automatic speech recognition corpus, BembaSpeech, consisting over 24 hours of read speech in the Bemba language, a written but low-resourced language spoken by over 30% of the population in Zambia. To assess its usefulness for training and testing ASR systems for Bemba, we explored different approaches; supervised pre-training (training from scratch), cross-lingual transfer learning from a monolingual English pre-trained model using DeepSpeech on the portion of the dataset and fine-tuning large scale self-supervised Wav2Vec2.0 based multilingual pre-trained models on the complete BembaSpeech corpus. From our experiments, the 1 billion XLS-R parameter model gives the best results. The model achieves a word error rate (WER) of 32.91%, results demonstrating that model capacity significantly improves performance and that multilingual pre-trained models transfers cross-lingual acoustic representation better than monolingual pre-trained English model on the BembaSpeech for the Bemba ASR. Lastly, results also show that the corpus can be used for building ASR systems for Bemba language.- Anthology ID:
- 2022.lrec-1.790
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 7277–7283
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.790
- DOI:
- Cite (ACL):
- Claytone Sikasote and Antonios Anastasopoulos. 2022. BembaSpeech: A Speech Recognition Corpus for the Bemba Language. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 7277–7283, Marseille, France. European Language Resources Association.
- Cite (Informal):
- BembaSpeech: A Speech Recognition Corpus for the Bemba Language (Sikasote & Anastasopoulos, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.lrec-1.790.pdf
- Code
- csikasote/BembaSpeech + additional community code
- Data
- JW300