Wav2vec2-base-timit-moaiz_explast Open-source Speech Recognition Model - Free Deployment for English Speech-to-Text Conversion

Wav2vec2 Base Timit Moaiz Explast

Developed by moaiz237

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base on the TIMIT dataset, primarily used for English speech-to-text tasks.

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #Low Word Error Rate #TIMIT Dataset

Downloads 19

Release Time : 4/30/2022

Model Overview

This is a speech recognition model based on the wav2vec2 architecture, fine-tuned on the TIMIT dataset, capable of converting English speech into text.

Model Features

Based on wav2vec2 Architecture

Utilizes the wav2vec2-base architecture developed by Facebook, featuring excellent speech feature extraction capabilities.

Fine-tuned on TIMIT Dataset

Fine-tuned on the TIMIT speech dataset, optimizing English speech recognition performance.

Relatively High Recognition Accuracy

Achieved a word error rate (WER) of 0.5404 on the evaluation set.

Model Capabilities

English Speech Recognition

Speech-to-Text

Use Cases

Speech Transcription

English Speech Transcription

Convert English speech content into text format

Word Error Rate 0.5404

Training Loss	Epoch	Step	Validation Loss	Wer
4.034	13.89	500	1.0507	0.6871
0.6024	27.78	1000	0.6714	0.5404

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Wav2vec2 Base Timit Moaiz Explast

Model Overview

Model Features

Model Capabilities

Use Cases

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Model description

Intended uses & limitations

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🔧 Technical Details

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