Automatic Speech Recognition
NeMo
PyTorch
English
speech
audio
CTC
Citrinet
Transformer
NeMo
hf-asr-leaderboard
Riva
Eval Results (legacy)
Instructions to use nvidia/stt_en_citrinet_1024_gamma_0_25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/stt_en_citrinet_1024_gamma_0_25 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/stt_en_citrinet_1024_gamma_0_25") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Commit ·
d136706
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Parent(s): d1314f7
Update README.md
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README.md
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@@ -10,7 +10,6 @@ datasets:
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- WSJ-1
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- National Singapore Corpus Part 1
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- National Singapore Corpus Part 6
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- mozilla-foundation/common_voice_7_0
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thumbnail: null
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tags:
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- automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value:
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value:
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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dataset:
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name: Multilingual LibriSpeech
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type: facebook/multilingual_librispeech
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config: english
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split: test
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args:
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language: en
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metrics:
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- name: Test WER
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type: wer
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value: 7.2
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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dataset:
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name: Mozilla Common Voice 7.0
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type: mozilla-foundation/common_voice_7_0
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config: en
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split: test
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args:
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language: en
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metrics:
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- name: Test WER
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type: wer
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value: 8.0
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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dataset:
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name: Mozilla Common Voice 8.0
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type: mozilla-foundation/common_voice_8_0
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config: en
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split: test
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args:
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language: en
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metrics:
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- name: Test WER
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type: wer
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value: 9.48
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 2.
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value:
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value:
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---
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# NVIDIA Streaming Citrinet 1024 (en-US)
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- Switchboard-1 Dataset
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- WSJ-0 and WSJ-1
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- National Speech Corpus (Part 1, Part 6)
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- Mozilla Common Voice (v7.0)
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Note: older versions of the model may have trained on smaller set of datasets.
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- WSJ-1
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- National Singapore Corpus Part 1
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- National Singapore Corpus Part 6
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thumbnail: null
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tags:
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- automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 3.4
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 7.6
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 2.5
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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value: 4.0
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- task:
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type: Automatic Speech Recognition
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name: automatic-speech-recognition
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metrics:
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- name: Test WER
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type: wer
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+
value: 6.2
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---
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# NVIDIA Streaming Citrinet 1024 (en-US)
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- Switchboard-1 Dataset
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- WSJ-0 and WSJ-1
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- National Speech Corpus (Part 1, Part 6)
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Note: older versions of the model may have trained on smaller set of datasets.
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