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Wav2vec2 Large Xls R 300m Turkish Colab
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Wav2vec2 Large Xls R 300m Turkish Colab
Developed by Khalsuu
This model is a speech recognition model fine-tuned on the Common Voice Turkish dataset based on facebook/wav2vec2-xls-r-300m, achieving a word error rate of 0.3907 on the evaluation set.
Downloads 22
Release Time : 3/24/2022
Model Overview
This is an automatic speech recognition (ASR) model optimized for Turkish, fine-tuned based on Facebook's wav2vec2-xls-r-300m architecture.
Model Features
Turkish optimization
Fine-tuned specifically for Turkish, improving recognition accuracy for Turkish speech.
Fine-tuned from a large model
Fine-tuned from Facebook's 300-million-parameter wav2vec2-xls-r large model, inheriting its powerful speech feature extraction capabilities.
Relatively low word error rate
Achieved a word error rate of 0.3907 on the evaluation set, demonstrating good performance.
Model Capabilities
Turkish speech recognition
Speech-to-text
Audio content transcription
Use Cases
Speech transcription
Turkish meeting minutes
Automatically transcribe Turkish meeting recordings into text records
Word error rate approximately 39%
Voice assistant
Speech recognition module for Turkish voice assistant applications
Education
Language learning applications
Help Turkish language learners check pronunciation accuracy
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