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Wav2vec2 Xls R 300m Urdu

Developed by aasem
Facebook's 300M parameter speech recognition model, fine-tuned for Urdu, trained on the Common Voice 8.0 Urdu dataset
Downloads 16
Release Time : 3/2/2022

Model Overview

This model is an automatic speech recognition (ASR) model based on the wav2vec2 architecture, specifically optimized for Urdu, capable of converting Urdu audio into text

Model Features

Urdu optimization
Specially fine-tuned for Urdu, delivering excellent performance in this language
Large-scale pretraining
Based on a 300M parameter large-scale pretrained model with powerful speech feature extraction capabilities
Efficient recognition
Achieves low word error rate and character error rate on the Common Voice dataset

Model Capabilities

Urdu audio to text conversion
Speech recognition
Speech transcription

Use Cases

Speech transcription
Urdu meeting minutes
Automatically convert Urdu meeting recordings into text transcripts
Word error rate 24.59%, character error rate 6.91%
Voice assistant
Provide voice interaction functionality for Urdu users
Education
Language learning assistance
Help Urdu learners with pronunciation assessment and transcription
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