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Wav2vec2 Base Timit Demo Colab
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Wav2vec2 Base Timit Demo Colab

Developed by Waynehillsdev
A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model, specializing in English speech-to-text tasks.
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition#Low Word Error Rate#TIMIT Dataset
Downloads 28
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of wav2vec2-base, specifically designed for English speech recognition tasks, trained on the TIMIT dataset and achieving a low word error rate.

Model Features

Low Word Error Rate
Achieved a word error rate (WER) of 0.3392 on the evaluation set, demonstrating excellent performance.
Based on Wav2Vec2 Architecture
Utilizes facebook's wav2vec2-base as the base model, featuring powerful speech feature extraction capabilities.
Efficient Training
Uses mixed-precision training and a linear learning rate scheduler for high training efficiency.

Model Capabilities

English Speech Recognition
Speech-to-Text
Audio Content Transcription

Use Cases

Speech Transcription
Meeting Minutes
Automatically convert English meeting recordings into text transcripts
Accuracy approximately 66% (based on WER 0.3392)
Voice Notes
Convert personal voice notes into searchable text
Assistive Technology
Real-time Caption Generation
Generate real-time captions for English video content
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