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Wav2vec2 Base Timit Demo Colab240
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Wav2vec2 Base Timit Demo Colab240

Developed by hassnain
A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on the TIMIT dataset
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition Fine-tuning#TIMIT Dataset#Low Word Error Rate
Downloads 16
Release Time : 5/1/2022

Model Overview

This model is an Automatic Speech Recognition (ASR) model primarily used for converting speech to text. Based on the wav2vec2 architecture, it is suitable for English speech recognition tasks.

Model Features

Efficient Fine-tuning
Fine-tuned based on the pre-trained wav2vec2-base model, improving performance on specific tasks
Lightweight
The base version is relatively small, suitable for deployment in resource-constrained environments
Mixed Precision Training
Uses native AMP for mixed precision training, enhancing training efficiency

Model Capabilities

English Speech Recognition
Speech-to-Text

Use Cases

Speech Transcription
Meeting Minutes
Automatically convert English meeting recordings into written transcripts
Word Error Rate 0.5855
Voice Notes
Convert English voice notes into searchable text
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