Bangla speech recognition: a 65.5M-parameter Zipformer transducer, fine-tuned from an English LibriSpeech model on about 1,210 hours of Bangla speech. CPU-friendly ONNX versions (fp32 / fp16 / int8): SayedShaun/bangla-zipformer-onnx. The model code comes from icefall, so you need to install it and a few packages once: Accepts a file path (wav / flac / ogg...) or (samples, samplerate). Don't want to install icefall and k2? Use the ONNX version, which needs only onnxruntime. asr.py is a thin wrapper. To use the weights directly, set up icefall as in the quick start (ICEFALLROOT), then: Full dev (5,282 utterances, 8.1 h) and test (10,485 utterances, 16.4 h) sets. WER counts punctuation…
Independent publisher
Sayed Shaun
SayedShaun
Deep Learning
Models in Library1
Datasets in Library0
Models on Hugging Face18
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Published tasks: Speech recognition.
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