facebook/wav2vec2-xls-r-300m fine-tuned on openslr (SLR86) and mozilla-foundation/common_voice_12_0 for Yoruba language.

WER: 0.51

```
from huggingsound import SpeechRecognitionModel

model = SpeechRecognitionModel("AstralZander/yoruba_ASR")
audio_paths = [audio_path] # List with paths to audio
transcriptions = model.transcribe(audio_paths)

transcriptions # List of transcriptions, timestamps and probabilities
transcriptions[ind_audio]['transcription'] # Transcription of audio with the ind_audio index from the audio_paths list
```
{"language": ["yo"], "license": "apache-2.0", "datasets": ["openslr", "mozilla-foundation/common_voice_12_0"]}
transformers pytorch wav2vec2 automatic-speech-recognition yo dataset:openslr dataset:mozilla-foundation/common_voice_12_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #yo #dataset-openslr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #endpoints_compatible #region-us 

facebook/wav2vec2-xls-r-300m fine-tuned on openslr (SLR86) and mozilla-foundation/common_voice_12_0 for Yoruba language.

WER: 0.51


TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #yo #dataset-openslr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #yo #dataset-openslr #dataset-mozilla-foundation/common_voice_12_0 #license-apache-2.0 #endpoints_compatible #region-us 
