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Wav2vec2 Base Timit Demo Colab90
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Wav2vec2 Base Timit Demo Colab90
Developed by hassnain
A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, specializing in English speech-to-text tasks
Downloads 16
Release Time : 5/1/2022
Model Overview
This model is a fine-tuned version of wav2vec2-base, optimized for speech recognition tasks, capable of converting English speech into text
Model Features
Efficient Fine-tuning
Fine-tuned based on the pre-trained wav2vec2-base model, achieving significant performance improvements with limited data
Low Word Error Rate
Achieved a word error rate (WER) of 0.4479 on the evaluation set, outperforming the base model
Lightweight Deployment
The base version is relatively small, making it suitable for deployment in resource-limited environments
Model Capabilities
English Speech Recognition
Speech-to-Text
Audio Content Transcription
Use Cases
Speech Transcription
Automated Meeting Minutes
Automatically convert English meeting recordings into text transcripts
Word error rate approximately 44.79%
Voice Note Conversion
Convert personal voice memos into searchable text
Assistive Tools
Hearing Impairment Assistance
Provide real-time speech-to-text services for individuals with hearing impairments
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