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Wav2vec2 Base 20sec Timit And Dementiabank
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Wav2vec2 Base 20sec Timit And Dementiabank

Developed by shields
A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on TIMIT and DementiaBank datasets, suitable for English speech recognition tasks.
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition Optimization#Medical Voice Analysis#Low Word Error Rate
Downloads 18
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of wav2vec2-base, focusing on English speech recognition, specifically optimized for TIMIT and DementiaBank datasets.

Model Features

Efficient Fine-tuning
Fine-tuned based on the wav2vec2-base model, achieving good recognition performance on specific datasets.
Low Word Error Rate
Achieved a word error rate (WER) of 0.2313 on the evaluation set, demonstrating good performance.
Mixed Precision Training
Used native AMP for mixed precision training, improving training efficiency.

Model Capabilities

English Speech Recognition
Audio to Text Conversion

Use Cases

Healthcare
Dementia Voice Analysis
Can be used to analyze voice characteristics of dementia patients
Speech Recognition Applications
English Speech Transcription
Convert English speech content into text
Word error rate 0.2313
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