Automatic Speech Recognition
Transformers
PyTorch
Hindi
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use nalini2799/CDAC_hindispeechrecognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nalini2799/CDAC_hindispeechrecognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nalini2799/CDAC_hindispeechrecognition")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nalini2799/CDAC_hindispeechrecognition") model = AutoModelForCTC.from_pretrained("nalini2799/CDAC_hindispeechrecognition") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"datasets[0]" with value "Interspeech 2021" is not valid. If possible, use a dataset id from https://hf.co/datasets.
Hindi-Speech to Text Model
The primary objective of this project is to develop a speech recognition system for the Hindi language. As there are very few systems available for speech to text in the Hindi language. Therefore it is an attempt to develop a system where a language model is developed using Machine learning libraries for speech-to-text conversion in the Hindi language.
- Downloads last month
- 10
Evaluation results
- Test WER on Common Voice hiself-reported72.730