Wav2vec2-1 Open-source Speech Recognition Model - Achieve Accurate Speech Recognition for Free

Wav2vec2 1

Developed by chrisvinsen

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.4949 on the evaluation set.

Downloads 16

Release Time : 5/22/2022

Model Overview

wav2vec2-1 is a speech recognition model based on the wav2vec2 architecture, primarily used for converting speech to text.

Based on wav2vec2 Architecture

Utilizes the advanced wav2vec2 architecture for speech recognition tasks.

Fine-tuned Optimization

Fine-tuned on the base model to improve recognition accuracy in specific scenarios.

Relatively Low Word Error Rate

Achieved a word error rate of 0.4949 on the evaluation set.

Speech-to-Text

Automatic Speech Recognition

Speech Transcription

Meeting Minutes

Automatically convert meeting recordings into text transcripts.

Voice Notes

Convert voice notes into editable text.

Assistive Technology

Hearing Assistance

Provide real-time speech-to-text services for the hearing impaired.

Property	Details
Model Type	Fine - tuned version of facebook/wav2vec2-base
License	Apache-2.0
Tags	generated_from_trainer

Training Loss	Epoch	Step	Validation Loss	Wer
4.2691	1.37	200	2.9045	1.0
1.6356	2.74	400	0.9277	0.8678
0.8062	4.11	600	0.8200	0.7776
0.5983	5.48	800	0.6829	0.7161
0.4863	6.85	1000	0.6205	0.6507
0.407	8.22	1200	0.6519	0.6763
0.3641	9.59	1400	0.5771	0.6088
0.3291	10.96	1600	0.6548	0.6202
0.2905	12.33	1800	0.6538	0.5828
0.2613	13.7	2000	0.6281	0.5864
0.2354	15.07	2200	0.5936	0.5630
0.2145	16.44	2400	0.5877	0.5699
0.2008	17.81	2600	0.5469	0.5488
0.1751	19.18	2800	0.6453	0.5584
0.169	20.55	3000	0.5871	0.5357
0.1521	21.92	3200	0.6063	0.5318
0.1426	23.29	3400	0.5609	0.5171
0.1287	24.66	3600	0.6056	0.5126
0.1236	26.03	3800	0.5994	0.5074
0.1138	27.4	4000	0.5980	0.4944
0.1083	28.77	4200	0.5980	0.4949

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