wav2vec2-base-timit-demo-colab Open Source Speech Recognition Model - Free Deployment for Precise Speech Content Recognition

Home

Wav2vec2 Base Timit Demo Colab

Developed by shumail

A fine-tuned speech recognition model based on facebook/wav2vec2-base, trained and evaluated on the TIMIT dataset.

Speech Recognition

Transformers

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

Downloads 24

Release Time : 4/30/2022

Model Overview

This model is a speech recognition model based on the wav2vec2 architecture, suitable for English speech-to-text tasks.

Model Features

Based on wav2vec2 Architecture

Uses facebook/wav2vec2-base as the base model, with excellent speech feature extraction capabilities.

Fine-tuning Optimization

Fine-tuned on the TIMIT dataset, improving recognition accuracy in specific scenarios.

Lightweight

Based on the base version, the model size is moderate and suitable for deployment in resource-limited environments.

Model Capabilities

English Speech Recognition

Speech-to-Text

Use Cases

Speech Transcription

Meeting Minutes

Convert English meeting recordings into text transcripts

Voice Notes

Convert personal voice notes into editable text

Education

Pronunciation Assessment

Used for pronunciation evaluation and correction for English learners

Training Loss	Epoch	Step	Validation Loss	Wer
5.0505	13.89	500	3.0760	1.0
1.2748	27.78	1000	0.8686	0.6263

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Wav2vec2 Base Timit Demo Colab

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-base-timit-demo-colab

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License