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Wav2vec2 Base Timit Demo Colab1
A speech recognition model fine-tuned from facebook/wav2vec2-base, trained on the TIMIT dataset
Downloads 25
Release Time : 4/29/2022
Model Overview
This is a speech recognition model based on the wav2vec2 architecture, primarily used for English speech-to-text tasks.
Model Features
Based on wav2vec2 Architecture
Utilizes Facebook's wav2vec2-base as the base model, featuring excellent speech feature extraction capabilities
Fine-tuning Optimization
Fine-tuned on the TIMIT dataset, optimized for specific speech recognition tasks
Moderate Performance
Achieves a word error rate (WER) of 0.56 on the evaluation set
Model Capabilities
English Speech Recognition
Audio to Text
Speech Content Analysis
Use Cases
Speech Transcription
Meeting Minutes
Convert English meeting recordings into text transcripts
Moderately accurate transcription results
Voice Notes
Convert personal voice memos into text
Suitable for personal use scenarios
Education
Pronunciation Assessment
Assist English learners in evaluating pronunciation accuracy
Can serve as an auxiliary tool for pronunciation practice
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