Instructions to use espnet/owsm_v4_base_102M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/owsm_v4_base_102M with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/owsm_v4_base_102M" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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[OWSM v4]() is the latest version in the OWSM series, which significantly outperforms OWSM v3.1 in LID and multilingual ASR.
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This repo contains a base-sized model with 102M parameters. It is trained on 320k hours of public speech data. It supports the following speech-to-text tasks:
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- Language identification
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- Speech recognition
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- Speech translation
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[OWSM v4]() is the latest version in the OWSM series, which significantly outperforms OWSM v3.1 in LID and multilingual ASR.
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This repo contains a base-sized model with 102M parameters, developed by [Yifan Peng](https://pyf98.github.io/) (CMU). It is trained on 320k hours of public speech data. It supports the following speech-to-text tasks:
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- Language identification
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- Speech recognition
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- Speech translation
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