
Fine-tuned on Multilingual Pretrained Model [CLSRIL-23](https://arxiv.org/abs/2107.07402). The original fairseq checkpoint is present [here](https://github.com/Open-Speech-EkStep/vakyansh-models). When using this model, make sure that your speech input is sampled at 16kHz.
**Note: The result from this model is without a language model so you may witness a higher WER in some cases.**

{"language": "pa", "license": "mit", "tags": ["audio", "automatic-speech-recognition", "speech"], "metrics": ["wer"], "model-index": [{"name": "Wav2Vec2 Vakyansh Punjabi Model by Harveen Chadha", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice hi", "type": "common_voice", "args": "pa"}, "metrics": [{"type": "wer", "value": 33.17, "name": "Test WER"}]}]}]}
transformers pytorch wav2vec2 automatic-speech-recognition audio speech pa arxiv:2107.07402 license:mit model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pa #arxiv-2107.07402 #license-mit #model-index #endpoints_compatible #has_space #region-us 


Fine-tuned on Multilingual Pretrained Model CLSRIL-23. The original fairseq checkpoint is present here. When using this model, make sure that your speech input is sampled at 16kHz.
Note: The result from this model is without a language model so you may witness a higher WER in some cases.

TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pa #arxiv-2107.07402 #license-mit #model-index #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #pa #arxiv-2107.07402 #license-mit #model-index #endpoints_compatible #has_space #region-us 
