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Wav2vec2 Base Timit Demo Colab 2
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Wav2vec2 Base Timit Demo Colab 2

Developed by fahadtouseef
A speech recognition model fine-tuned based on facebook/wav2vec2-base, demonstrating excellent performance on the TIMIT dataset
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition#Low Word Error Rate#TIMIT Dataset
Downloads 24
Release Time : 5/2/2022

Model Overview

This model is a fine-tuned version of wav2vec2-base, specialized for English speech recognition tasks with a low word error rate.

Model Features

Low Word Error Rate
Achieves a word error rate (WER) of 0.3035 on the evaluation set, demonstrating outstanding performance
Based on wav2vec2 Architecture
Utilizes facebook's wav2vec2-base as the foundation model, featuring powerful speech feature extraction capabilities
Efficient Training
Employs mixed-precision training (native AMP) and a linear learning rate scheduler to optimize training efficiency

Model Capabilities

English Speech Recognition
Audio to Text Conversion
Continuous Speech Recognition

Use Cases

Speech Transcription
Meeting Minutes
Automatically convert meeting recordings into text transcripts
Approximately 70% accuracy (inferred based on WER 0.3035)
Voice Assistant
Serves as the foundational recognition component for voice assistants
Education
Pronunciation Assessment
Used for evaluating pronunciation accuracy in language learning
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