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AI4Bharat-IndicConformer-STT-UR-Hybrid-CTC-RNNT-Large (Urdu): Automatic Speech Recognition Model

An Automatic Speech Recognition (ASR) model for Urdu, built using the IndicConformer architecture with a Hybrid CTC-RNNT approach for accurate and efficient transcription.

About Model

The AI4Bharat IndicConformer-STT-UR-Hybrid-CTC-RNNT-Large model is an advanced Automatic Speech Recognition (ASR) system designed to transcribe Urdu speech to text. It uses the IndicConformer architecture, which integrates Conformer-based feature extraction with the powerful Hybrid CTC-RNNT (Connectionist Temporal Classification - Recurrent Neural Network Transducer) approach. This architecture enables robust transcription performance, even in noisy environments and for diverse speech patterns. The model is ideal for applications in voice-driven interfaces, transcription services, accessibility solutions, and multilingual ASR systems, providing a reliable solution for recognizing Urdu speech.

AI4Bharat-IndicConformer-STT-UR-Hybrid-CTC-RNNT-Large (Urdu): Automatic Speech Recognition Model

Metadata Metadata

MIT

AI4Bharat

Audio-to-text

N.A.

Open

AI4Bharat

Sector Agnostic

21/02/25 13:21:27

0

Activity Overview Activity Overview

  • Downloads0
  • Redirect 12
  • Views 303
  • File Size 0

Tags Tags

  • Automatic Speech Recognition
  • ASR
  • Urdu
  • Speech-to-Text
  • IndicConformer
  • Hybrid-CTC-RNNT
  • Deep Learning
  • multilingual-ASR
  • transcription
  • voice-to-text

License Control License Control

MIT

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