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Home/Models/AI4Bharat- IndicConformerAutomatic Speech Recognition (ASR) Model for Dogri

AI4Bharat- IndicConformerAutomatic Speech Recognition (ASR) Model for Dogri

The Dogri ASR (Automatic Speech Recognition) model transcribes 16kHz mono-channel audio into text. It is based on a Conformer-Large architecture with 120M parameters and a hybrid CTC-RNNT decoder, ensuring accurate and efficient speech-to-text conversion

About Model

The Dogri ASR (Automatic Speech Recognition) model is designed to convert spoken Dogri into text from 16kHz mono-channel audio files. It is built on a Conformer-Large architecture with 120 million parameters, providing high accuracy in speech recognition. The model utilizes a hybrid CTC-RNNT decoder to improve transcription quality. With 17 conformer blocks and a model dimension of 512, it effectively captures linguistic and acoustic features, making it ideal for speech-to-text applications in Dogri.

AI4Bharat- IndicConformerAutomatic Speech Recognition (ASR) Model for Dogri

Metadata Metadata

MIT

AI4Bharat

Automatic Speech Recognition

N.A.

Open

AI4Bharat

Sector Agnostic

21/02/25 13:21:47

Nikhil Narasimhan

0

Activity Overview Activity Overview

  • Downloads0
  • Redirect 11
  • File Size 0
  • Views 427

Tags Tags

  • Automatic Speech Recognition
  • Audio Processing
  • NLP
  • Speech-to-Text

License Control License Control

MIT

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