Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages
This addresses the problem of underrepresentation in ASR for low-resource language communities, though it is incremental as it focuses on dataset creation and baseline models.
The authors tackled the lack of ASR resources for low-resource languages by creating and releasing an open-licensed dataset of Bible audio recordings in northern Indian languages, and they established baselines by training and analyzing two competitive ASR models on this data.
Automatic Speech Recognition (ASR) has increasing utility in the modern world. There are a many ASR models available for languages with large amounts of training data like English. However, low-resource languages are poorly represented. In response we create and release an open-licensed and formatted dataset of audio recordings of the Bible in low-resource northern Indian languages. We setup multiple experimental splits and train and analyze two competitive ASR models to serve as the baseline for future research using this data.