**wav2vec2-base-timit-demo-colab2 Open-Source Speech Recognition Model - Precise Speech Content Recognition with Low Error Rate**

Wav2vec2 Base Timit Demo Colab2

Developed by sherry7144

A fine-tuned speech recognition model based on facebook/wav2vec2-base, trained on the TIMIT dataset with a word error rate of 0.5855

Downloads 24

Release Time : 5/1/2022

Model Overview

This model is an Automatic Speech Recognition (ASR) system for English, fine-tuned based on the wav2vec2 architecture

Efficient Fine-tuning

Fine-tuned based on the pre-trained wav2vec2-base model with high training efficiency

Moderate Word Error Rate

Achieves a word error rate (WER) of 0.5855 on the evaluation set

Lightweight

Based on the base version of wav2vec2, relatively lightweight

English Speech Recognition

Audio to Text Conversion

Speech Transcription

Meeting Minutes

Convert English meeting recordings into text transcripts

Moderately accurate transcription results

Voice Notes

Convert personal voice memos into text

Training Loss	Epoch	Step	Validation Loss	Wer
5.1452	13.89	500	2.9679	1.0
1.075	27.78	1000	0.7746	0.5855

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