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Aradia Ctc Hubert Ft
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Aradia Ctc Hubert Ft

Developed by abdusah
Arabic automatic speech recognition model based on HuBERT architecture, fine-tuned on a 300-hour Arabic speech dataset
Speech Recognition
Transformers
#Arabic speech recognition#HuBERT fine-tuning#Large-scale speech dataset
Downloads 30
Release Time : 3/31/2022

Model Overview

This model is an Arabic automatic speech recognition model optimized with CTC loss function based on the HuBERT architecture. It was fine-tuned on a large-scale 300-hour Arabic speech dataset, primarily used for converting Arabic speech to text.

Model Features

Large-scale Arabic training
Trained on a 300-hour Arabic speech dataset, covering a wide range of speech scenarios
HuBERT architecture optimization
Based on the HuBERT self-supervised learning architecture, optimized with CTC loss function
Relatively low word error rate
Achieves a word error rate (WER) of 0.3737 on the evaluation set

Model Capabilities

Arabic speech recognition
Continuous speech-to-text
Large-scale speech processing

Use Cases

Speech transcription
Arabic meeting minutes
Automatically convert Arabic meeting recordings into text transcripts
Word error rate approximately 37%
Voice assistant
Provide speech recognition capabilities for Arabic voice assistants
Education
Language learning applications
Help learners practice Arabic pronunciation and listening
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