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Wav2vec2 Base Timit Ali Hasan Colab EX2

Developed by ali221000262
A speech recognition model fine-tuned from facebook/wav2vec2-base on the TIMIT dataset, with a WER of 0.4458 on the evaluation set
Downloads 23
Release Time : 4/30/2022

Model Overview

This model is a speech recognition model based on the wav2vec2 architecture, suitable for English speech-to-text tasks

Model Features

Efficient Fine-tuning
Fine-tuned from the pre-trained wav2vec2-base model, improving performance on specific tasks
Medium Scale
Uses the base-scale wav2vec2 architecture, balancing performance and computational resource requirements

Model Capabilities

English Speech Recognition
Speech-to-Text

Use Cases

Speech Transcription
Meeting Minutes
Convert English meeting recordings into text transcripts
Word Error Rate 0.4458
Voice Notes
Convert English voice memos into text
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