Wav2vec2-300m-teste4 Open Source Speech Recognition Model - Free Deployment for Accurate Speech Content Recognition

Home

Wav2vec2 300m Teste4

Developed by tonyalves

A speech recognition model fine-tuned on the common_voice dataset based on facebook/wav2vec2-xls-r-300m

Speech Recognition

Transformers

Open Source License:Apache-2.0 #Speech Recognition #Multilingual Support #Low Word Error Rate

Downloads 17

Release Time : 3/2/2022

Model Overview

This is a model for Automatic Speech Recognition (ASR), based on the wav2vec2-xls-r-300m architecture and fine-tuned on the common_voice dataset.

Model Features

Efficient Speech Recognition

Fine-tuned on the common_voice dataset with good speech recognition capabilities

Based on wav2vec2 Architecture

Uses facebook's wav2vec2-xls-r-300m pre-trained model as the base

Optimized Training

Trained for 4 epochs with techniques like mixed-precision training

Model Capabilities

Speech to Text

Automatic Speech Recognition

Use Cases

Speech Transcription

Speech to Text

Convert speech content into text transcripts

Word Error Rate 0.3489

Voice Assistant

Voice Command Recognition

Recognize user voice commands

Training Loss	Epoch	Step	Validation Loss	Wer
10.0237	0.49	100	4.2075	0.9792
3.313	0.98	200	3.0232	0.9792
2.9469	1.47	300	2.7591	0.9792
1.4217	1.96	400	0.8397	0.6219
0.5598	2.45	500	0.6085	0.5087
0.4507	2.94	600	0.4512	0.4317
0.2775	3.43	700	0.3839	0.3751
0.2047	3.92	800	0.3276	0.3489

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 300m Teste4

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-300m-teste4

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License