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Register a new userA ResNet-50-Based Convolutional Neural Network Model for Language ID Identification from Speech Recordings
نموذج شبكة عصبي NEVERTAL NEWRELTAL يستند إلى HernNet-50 للحصول على تحديد معرف اللغة من تسجيلات الكلام
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تصف هذه الورقة النموذج المدمج للمهمة المشتركة SIGTYP 2021 التي تهدف إلى تحديد 18 لغة مختلفة عن تسجيلات الكلام.يتم تحويل معاملات CEPSTRAL Mel-تردد Mel المستمدة من الملفات الصوتية إلى طفرات، ثم تغذيها بعد ذلك في بنية CNN المستند إلى 50.حصل النموذج النهائي على التحقق من الصحة واختبار بدلة 0.73 و 0.53، على التوالي.
This paper describes the model built for the SIGTYP 2021 Shared Task aimed at identifying 18 typologically different languages from speech recordings. Mel-frequency cepstral coefficients derived from audio files are transformed into spectrograms, which are then fed into a ResNet-50-based CNN architecture. The final model achieved validation and test accuracies of 0.73 and 0.53, respectively.
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