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BembaSpeech: A Speech Recognition Corpus for the Bemba Language

2021-02-09 15:42:00
Claytone Sikasote, Antonios Anastasopoulos
arXiv_CL
       
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 train an end-to-end Bemba ASR system by fine-tuning a pre-trained DeepSpeech English model on the training portion of the BembaSpeech corpus. Our best model achieves a word error rate (WER) of 54.78%. The results show that the corpus can be used for building ASR systems for Bemba. The corpus and models are publicly released at this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2102.04889

PDF

https://arxiv.org/pdf/2102.04889.pdf

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