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---
language:
- ja
license: apache-2.0
tags:
- audio
- automatic-speech-recognition
- speech
datasets:
- Japanese accent datasets
metrics:
- wer
# Optional. Add this if you want to encode your eval results in a structured way.
model-index:
- name: Wav2vec2 Accent Japanese
results:
- task:
type: Speech Recognition # Required. Example: automatic-speech-recognition
name: automatic-speech-recognition # Optional. Example: Speech Recognition
dataset:
type: accent_voice
name: Japanese accent datasets
args: ja
metrics:
- type: wer # Required.
value: 15.82 # Required.
name: Test WER
---
# Wav2Vec2 Accent Japanese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Japanese accent dataset
When using this model, make sure that your speech input is sampled at 16kHz.
## Test Result
WER: 15.82% |