wav2vec2-base-timit-demo-colab4 Open-source Speech Recognition Model

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Wav2vec2 Base Timit Demo Colab4

Developed by sameearif88

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

Speech Recognition

Transformers

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

Downloads 16

Release Time : 5/1/2022

Model Overview

This is a speech recognition model based on the wav2vec2 architecture, specifically optimized for English speech recognition tasks.

Model Features

Efficient Speech Recognition

Based on the wav2vec2 architecture, providing efficient speech-to-text capabilities

Fine-tuning Optimization

Specially fine-tuned on the TIMIT dataset to improve recognition accuracy

Lightweight Base Model

Based on the wav2vec2-base architecture, relatively lightweight and efficient

Model Capabilities

English Speech Recognition

Audio to Text

Speech Content Analysis

Use Cases

Speech Transcription

Meeting Minutes Transcription

Automatically convert English meeting recordings into text transcripts

Word Error Rate 0.5907

Voice Note Conversion

Convert English voice notes into searchable text

Training Loss	Epoch	Step	Validation Loss	Wer
4.9363	13.89	500	2.7532	1.0
0.9875	27.78	1000	0.9149	0.5907

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Wav2vec2 Base Timit Demo Colab4

Model Overview

Model Features

Model Capabilities

Use Cases

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Model description

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Training and evaluation data

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