# exp_w2v2t_it_unispeech-ml_s246

Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (it)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.

This model has been fine-tuned by the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) tool.
    
{"language": ["it"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "it"], "datasets": ["mozilla-foundation/common_voice_7_0"]}
transformers pytorch unispeech automatic-speech-recognition it dataset:mozilla-foundation/common_voice_7_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #it #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us 

# exp_w2v2t_it_unispeech-ml_s246

Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (it).
When using this model, make sure that your speech input is sampled at 16kHz.

This model has been fine-tuned by the HuggingSound tool.
    
# exp_w2v2t_it_unispeech-ml_s246

Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (it).
When using this model, make sure that your speech input is sampled at 16kHz.

This model has been fine-tuned by the HuggingSound tool.
TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #it #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us 
 # exp_w2v2t_it_unispeech-ml_s246

Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (it).
When using this model, make sure that your speech input is sampled at 16kHz.

This model has been fine-tuned by the HuggingSound tool.
passage: TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #it #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us 
# exp_w2v2t_it_unispeech-ml_s246

Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (it).
When using this model, make sure that your speech input is sampled at 16kHz.

This model has been fine-tuned by the HuggingSound tool.