Automatic Speech Recognition
NeMo
PyTorch
automatic-speech-translation
speech
audio
Transformer
FastConformer
Conformer
NeMo
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use nvidia/canary-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/canary-1b with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/canary-1b") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Update README.md
#19
by steveheh - opened
README.md
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@@ -331,8 +331,8 @@ Another recommended option is to use a json manifest as input, where each line i
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio
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"taskname": "asr", # use "
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"source_lang": "en", # language of the audio input, set `source_lang`==`target_lang` for ASR, choices=['en','de','es','fr']
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"target_lang": "en", # language of the text output, choices=['en','de','es','fr']
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"pnc": "yes", # whether to have PnC output, choices=['yes', 'no']
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@@ -364,7 +364,7 @@ An example manifest for transcribing English audios can be:
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio
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"taskname": "asr",
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"source_lang": "en", # language of the audio input, set `source_lang`==`target_lang` for ASR, choices=['en','de','es','fr']
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"target_lang": "en", # language of the text output, choices=['en','de','es','fr']
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@@ -382,8 +382,8 @@ An example manifest for transcribing English audios into German text can be:
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio
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"taskname": "
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"source_lang": "en", # language of the audio input, choices=['en','de','es','fr']
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"target_lang": "de", # language of the text output, choices=['en','de','es','fr']
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"pnc": "yes", # whether to have PnC output, choices=['yes', 'no']
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio, can be set to `None` if using NeMo main branch
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"taskname": "asr", # use "s2t_translation" for speech-to-text translation with r1.23, or "ast" if using the NeMo main branch
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"source_lang": "en", # language of the audio input, set `source_lang`==`target_lang` for ASR, choices=['en','de','es','fr']
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"target_lang": "en", # language of the text output, choices=['en','de','es','fr']
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"pnc": "yes", # whether to have PnC output, choices=['yes', 'no']
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio, can be set to `None` if using NeMo main branch
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"taskname": "asr",
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"source_lang": "en", # language of the audio input, set `source_lang`==`target_lang` for ASR, choices=['en','de','es','fr']
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"target_lang": "en", # language of the text output, choices=['en','de','es','fr']
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# Example of a line in input_manifest.json
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{
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"audio_filepath": "/path/to/audio.wav", # path to the audio file
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"duration": 1000, # duration of the audio, can be set to `None` if using NeMo main branch
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"taskname": "s2t_translation", # r1.23 only recognizes "s2t_translation", but "ast" is supported if using the NeMo main branch
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"source_lang": "en", # language of the audio input, choices=['en','de','es','fr']
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"target_lang": "de", # language of the text output, choices=['en','de','es','fr']
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"pnc": "yes", # whether to have PnC output, choices=['yes', 'no']
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