# Wav2Vec2-XLS-R-300M-Japanese-Hiragana
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on Japanese Hiragana characters using JSUT, JVS, Common Voice, and in-house dataset.
The sentence outputs do not contain word boundaries. Audio inputs should be sampled at 16kHz.

## Test Results
**CER:** 9.34%
## Training
Trained on JSUT, a subset of JVS, train+valid set of Common Voice Japanese, and in-house Japanese dataset. Tested on test set of Common Voice Japanese.
{"language": "ja", "datasets": ["common_voice"], "metrics": ["cer"], "model-index": [{"name": "wav2vec2-xls-r-300m finetuned on Japanese Hiragana with no word boundaries", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice Japanese", "type": "common_voice", "args": "ja"}, "metrics": [{"type": "cer", "value": 9.34, "name": "Test CER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition ja dataset:common_voice model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ja #dataset-common_voice #model-index #endpoints_compatible #region-us 

# Wav2Vec2-XLS-R-300M-Japanese-Hiragana
Fine-tuned facebook/wav2vec2-xls-r-300m on Japanese Hiragana characters using JSUT, JVS, Common Voice, and in-house dataset.
The sentence outputs do not contain word boundaries. Audio inputs should be sampled at 16kHz.

## Test Results
CER: 9.34%
## Training
Trained on JSUT, a subset of JVS, train+valid set of Common Voice Japanese, and in-house Japanese dataset. Tested on test set of Common Voice Japanese.
# Wav2Vec2-XLS-R-300M-Japanese-Hiragana
Fine-tuned facebook/wav2vec2-xls-r-300m on Japanese Hiragana characters using JSUT, JVS, Common Voice, and in-house dataset.
The sentence outputs do not contain word boundaries. Audio inputs should be sampled at 16kHz. ## Test Results
CER: 9.34% ## Training
Trained on JSUT, a subset of JVS, train+valid set of Common Voice Japanese, and in-house Japanese dataset. Tested on test set of Common Voice Japanese.
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ja #dataset-common_voice #model-index #endpoints_compatible #region-us 
 # Wav2Vec2-XLS-R-300M-Japanese-Hiragana
Fine-tuned facebook/wav2vec2-xls-r-300m on Japanese Hiragana characters using JSUT, JVS, Common Voice, and in-house dataset.
The sentence outputs do not contain word boundaries. Audio inputs should be sampled at 16kHz. ## Test Results
CER: 9.34% ## Training
Trained on JSUT, a subset of JVS, train+valid set of Common Voice Japanese, and in-house Japanese dataset. Tested on test set of Common Voice Japanese.
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ja #dataset-common_voice #model-index #endpoints_compatible #region-us 
# Wav2Vec2-XLS-R-300M-Japanese-Hiragana
Fine-tuned facebook/wav2vec2-xls-r-300m on Japanese Hiragana characters using JSUT, JVS, Common Voice, and in-house dataset.
The sentence outputs do not contain word boundaries. Audio inputs should be sampled at 16kHz.## Test Results
CER: 9.34%## Training
Trained on JSUT, a subset of JVS, train+valid set of Common Voice Japanese, and in-house Japanese dataset. Tested on test set of Common Voice Japanese.