OOD-Speech: A Large Bengali Speech Recognition Dataset for Out-of-Distribution Benchmarking
Paper • 2305.09688 • Published • 1
Datasets:
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Bengali Speech Recognition
Transcribe short Bengali utterances. Training clips carry transcripts; held-out clips do not, and their references are not in this dataset. Audio is 16 kHz mono mp3 at 48 kbps.
Contents
The data tree lives under data/, exactly as the benchmark environment presents it at
/app/bnspeech. Its own description is at data/README.md.
- 5 files, 1916446809 bytes (1.8 GiB)
- structure hash (sha256 over sorted
path\tsizelines):4f0422e65a3547d42c09276d3e8cf1621eb20e7af1737bfd23993b12c072560d data.manifest.tsvat the repo root lists every file assha256 size path
Use
from huggingface_hub import snapshot_download
snapshot_download("Emulated-Inc/bnspeech", repo_type="dataset", revision="REVISION",
local_dir="./bnspeech", allow_patterns="data/*")
Pin revision to a commit sha rather than a branch if you need reproducibility.
Provenance and licence
Derived from the Bengali.AI Speech Recognition Kaggle competition training corpus (https://www.kaggle.com/competitions/bengaliai-speech), released under CC BY 4.0. Attribution to Bengali.AI and the OOD-Speech dataset authors (Rakib et al., "OOD-Speech: A Large Bengali Speech Recognition Dataset for Out-of-Distribution Benchmarking", Interspeech 2023, arXiv:2305.09688) and the Mozilla Common Voice Bengali contributors. This is a curated, re-encoded subset with opaque ids and normalized transcripts; the held-out split is carved from the competition's public training data.
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