wav2vec2-base-demo-colab Open-source Speech Recognition Model - Complete Training for Free in Colab Environment

Wav2vec2 Base Demo Colab

Developed by thyagosme

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, trained in a Colab environment

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Release Time : 3/2/2022

Model Overview

A fine-tuned model for speech recognition tasks, based on the wav2vec2 architecture, suitable for converting speech to text

Efficient Fine-tuning

Fine-tuned on the base model, significantly improving recognition accuracy in specific scenarios

Low Word Error Rate

Achieved a word error rate (WER) of 0.3422 on the evaluation set

Colab Compatible

The model was trained in a Google Colab environment, making it suitable for deployment in similar environments

Speech-to-Text

Automatic Speech Recognition

Audio Content Transcription

Speech Transcription

Automated Meeting Minutes

Automatically convert meeting recordings into text transcripts

Word error rate 0.3422

Voice Command Recognition

Recognize and convert voice commands into executable commands

Training Loss	Epoch	Step	Validation Loss	Wer
3.4477	4.0	500	1.3352	0.9039
0.5972	8.0	1000	0.4752	0.4509
0.2224	12.0	1500	0.4604	0.4052
0.1308	16.0	2000	0.4542	0.3866
0.0889	20.0	2500	0.4730	0.3589
0.0628	24.0	3000	0.4984	0.3657
0.0479	28.0	3500	0.4657	0.3422

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