  Bengali is one of the most spoken languages in the world with over 300
million speakers globally. Despite its popularity, research into the
development of Bengali speech recognition systems is hindered due to the lack
of diverse open-source datasets. As a way forward, we have crowdsourced the
Bengali Common Voice Speech Dataset, which is a sentence-level automatic speech
recognition corpus. Collected on the Mozilla Common Voice platform, the dataset
is part of an ongoing campaign that has led to the collection of over 400 hours
of data in 2 months and is growing rapidly. Our analysis shows that this
dataset has more speaker, phoneme, and environmental diversity compared to the
OpenSLR Bengali ASR dataset, the largest existing open-source Bengali speech
dataset. We present insights obtained from the dataset and discuss key
linguistic challenges that need to be addressed in future versions.
Additionally, we report the current performance of a few Automatic Speech
Recognition (ASR) algorithms and set a benchmark for future research.
