Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi
This work addresses the problem of limited linguistic data for low-resource languages, benefiting researchers and communities, but it is incremental as it applies existing methods to new data.
The paper tackles the lack of speech resources for low-resource Indian languages by developing an annotated speech corpus of approximately 18 hours for Awadhi, Bhojpuri, Braj, and Magahi, and reports baseline results for automatic speech recognition systems in these languages.
In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection. The total size of the corpus currently stands at approximately 18 hours (approx. 4-5 hours each language) and it is transcribed and annotated with grammatical information such as part-of-speech tags, morphological features and Universal dependency relationships. We discuss our methodology for data collection in these languages, most of which was done in the middle of the COVID-19 pandemic, with one of the aims being to generate some additional income for low-income groups speaking these languages. In the paper, we also discuss the results of the baseline experiments for automatic speech recognition system in these languages.