wav2vec2-base-timit-demo-colab Open-source Speech Recognition Model - Accurately Recognize Speech Content for Free

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Wav2vec2 Base Timit Demo Colab

Developed by ali221000262

A speech recognition model fine-tuned on the TIMIT dataset based on the wav2vec2-base model

Speech Recognition

Transformers

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

Downloads 23

Release Time : 4/30/2022

Model Overview

This model is a speech recognition model based on the wav2vec2-base architecture, fine-tuned on the TIMIT dataset, suitable for English speech recognition tasks.

Model Features

Based on wav2vec2 Architecture

Utilizes Facebook AI's wav2vec2-base architecture, which has excellent speech feature extraction capabilities

Fine-tuned on TIMIT Dataset

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

Lightweight Model

Based on the base version, suitable for deployment in resource-limited environments

Model Capabilities

English Speech Recognition

Audio to Text Conversion

Use Cases

Speech Transcription

English Speech Transcription

Convert English speech content into text

Word Error Rate (WER) of 1.0 on the evaluation set

Educational Applications

English Pronunciation Assessment

Can be used in pronunciation assessment systems for English learners

Training Loss	Epoch	Step	Validation Loss	Wer
2.6432	13.89	500	3.2161	1.0

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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

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📄 License