Audio Classification to Speech and Music using SVM and MLP
Publish Year: 1393
Type: Conference paper
Language: English
View: 880
This Paper With 5 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
ICEEE06_126
Index date: 23 September 2015
Audio Classification to Speech and Music using SVM and MLP abstract
In this paper, the performance of some features based on wavelet transform are evaluated through classification of audio to speech and music using both the SVM and the MLP classifiers. The wavelet features compared to typical MFCC features as input into an audio classifier. Classification results show the wavelet features are quite successful in speech/music classification. Experimental comparisons using different wavelets are presented and discussed. By using some wavelet features, extracted from 1-second segments of the signal, we achieved 97.19% accuracy in the audio classification.
Audio Classification to Speech and Music using SVM and MLP Keywords:
Audio Classification to Speech and Music using SVM and MLP authors
Foad Rahimzadeh Tabrizi
Islamic Azad University, Gonabad branch, Iran
Emad Abbasi Seidabad
Islamic Azad University, Gonabad branch, Iran
Jalil Shirazi
Islamic Azad University, Gonabad branch, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :