Open-source Speech Recognition Model wav2vec2-base-timit-demo-colab_3

Wav2vec2 Base Timit Demo Colab 3

Developed by fahadtouseef

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 25

Release Time : 5/2/2022

Model Overview

A speech recognition model based on the wav2vec2 architecture, fine-tuned on the TIMIT dataset, suitable for English speech-to-text tasks.

Model Features

Efficient Fine-tuning

Fine-tuned based on the pre-trained wav2vec2-base model, achieving excellent results on the TIMIT dataset.

Low Word Error Rate

Achieved a word error rate (WER) of 1.0 on the evaluation set, demonstrating outstanding performance.

Model Capabilities

English Speech Recognition

Speech-to-Text

Use Cases

Speech Processing

Speech Transcription

Convert English speech content into text

Word error rate 1.0

Training Loss	Epoch	Step	Validation Loss	Wer
4.2975	3.52	500	3.1771	1.0
3.1468	7.04	1000	3.1917	1.0
3.147	10.56	1500	3.1784	1.0
3.1467	14.08	2000	3.1850	1.0
3.1446	17.61	2500	3.2022	1.0
3.1445	21.13	3000	3.2196	1.0
3.1445	24.65	3500	3.2003	1.0
3.1443	28.17	4000	3.1942	1.0

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 3

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 wav2vec2-base-timit-demo-colab_3

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License