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Wav2vec2 Large Xls R 300m Turkish Colab
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Wav2vec2 Large Xls R 300m Turkish Colab

Developed by dperezjr
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 30.36% on the evaluation set.
Speech Recognition
Transformers
Open Source License:Apache-2.0#Turkish speech recognition#Large model fine-tuning#Low word error rate
Downloads 96
Release Time : 6/30/2022

Model Overview

This is an automatic speech recognition (ASR) model optimized for Turkish, fine-tuned based on Facebook's wav2vec2-xls-r-300m architecture, suitable for Turkish speech-to-text tasks.

Model Features

Turkish optimization
Specially fine-tuned for Turkish, outperforming general speech recognition models on this language
Based on XLS-R architecture
Utilizes Facebook's powerful wav2vec2-xls-r-300m architecture with robust speech feature extraction capabilities
Low word error rate
Achieves a word error rate of 30.36% on the evaluation set, demonstrating good performance for a language-specific model

Model Capabilities

Turkish speech recognition
Speech-to-text
Audio content transcription

Use Cases

Speech transcription
Turkish meeting minutes
Automatically convert Turkish meeting recordings into text transcripts
Approximately 70% accuracy (inferred from the 30.36% word error rate)
Voice assistant
Provide speech recognition capabilities for Turkish voice assistants
Educational applications
Language learning aid
Assist Turkish language learners in checking pronunciation accuracy
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