
training on full commonvoice

The WERs are:

| decoding method      | chunk size |  test  |        comment       |     decoding mode    |
| -------------------- | ---------- | ------ | -------------------- | -------------------- |
| greedy search        | 640ms      | 10.90  | --epoch 30 --avg 9   | simulated streaming  |
| modified beam search | 640ms      | 10.55  | --epoch 30 --avg 9   | simulated streaming  |
| fast beam search     | 640ms      | 10.75  | --epoch 30 --avg 9   | simulated streaming  |

training on full librispeech then finetune on full commonvoice

The WERs are:

| decoding method      | chunk size |  test  |        comment       |     decoding mode    |
| -------------------- | ---------- | ------ | -------------------- | -------------------- |
| greedy search        | 640ms      | 10.57  | --epoch 29 --avg 9   | simulated streaming  |
| modified beam search | 640ms      | 10.19  | --epoch 29 --avg 9   | simulated streaming  |
| fast beam search     | 640ms      | 10.25  | --epoch 29 --avg 9   | simulated streaming  |

training on full librispeech and gigaspeech then finetune on full commonvoice

The WERs are:

| decoding method      | chunk size |  test  |        comment       |     decoding mode    |
| -------------------- | ---------- | ------ | -------------------- | -------------------- |
| greedy search        | 640ms      | 9.95   | --epoch 30 --avg 9   | simulated streaming  |
| modified beam search | 640ms      | 9.57   | --epoch 30 --avg 9   | simulated streaming  |
| fast beam search     | 640ms      | 9.67   | --epoch 30 --avg 9   | simulated streaming  |


{"language": ["fr"], "license": "apache-2.0", "datasets": ["mozilla-foundation/common_voice_12_0"], "metrics": ["wer"], "pipeline_tag": "automatic-speech-recognition"}
tensorboard automatic-speech-recognition fr dataset:mozilla-foundation/common_voice_12_0 license:apache-2.0 region:us
TAGS
#tensorboard #automatic-speech-recognition #fr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #region-us 

training on full commonvoice


The WERs are:



training on full librispeech then finetune on full commonvoice


The WERs are:



training on full librispeech and gigaspeech then finetune on full commonvoice


The WERs are:




TAGS
#tensorboard #automatic-speech-recognition #fr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #region-us 

TAGS
#tensorboard #automatic-speech-recognition #fr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #region-us 
