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Wav2vec2 Base Timit Ali Hasan Colab
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Wav2vec2 Base Timit Ali Hasan Colab

Developed by ali221000262
A speech recognition model fine-tuned from facebook/wav2vec2-base, trained on the TIMIT dataset
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition#Low Word Error Rate#TIMIT Dataset
Downloads 25
Release Time : 4/30/2022

Model Overview

This model is a fine-tuned version of wav2vec2-base, specialized for English speech recognition tasks. Although the model card information is limited, based on its foundational architecture and training data, it is likely suitable for English speech-to-text applications.

Model Features

Based on wav2vec2 Architecture
Utilizes Facebook's wav2vec2-base as the foundational model, featuring robust speech feature extraction capabilities
Fine-tuned on TIMIT Dataset
Fine-tuned on the TIMIT English speech dataset, potentially making it more suitable for English speech recognition tasks
Lightweight Model
Based on the wav2vec2-base architecture, it is more lightweight compared to larger models, making it suitable for resource-constrained environments

Model Capabilities

English Speech Recognition
Speech-to-Text

Use Cases

Speech Transcription
English Speech Transcription
Convert English speech content into text
Word Error Rate (WER) of 1.0 (based on evaluation set)
Educational Applications
English Pronunciation Assessment
Can be used in pronunciation assessment systems for English learners
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