این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Journal of Artificial Intelligence and Data Mining، جلد ۱۰، شماره ۴، صفحات ۵۳۹-۵۴۷
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Speech Emotion Recognition using Enriched Spectrogram and Deep Convolutional Neural Network Transfer Learning
چکیده انگلیسی مقاله Speech emotion recognition (SER) is a challenging field of research that has attracted attention during the last two decades. Feature extraction has been reported as the most challenging issue in SER systems. Deep neural networks could partially solve this problem in some other applications. In order to address this problem, we proposed a novel enriched spectrogram calculated based on the fusion of wide-band and narrow-band spectrograms. The proposed spectrogram benefited from both high temporal and spectral resolution. Then we applied the resultant spectrogram images to the pre-trained deep convolutional neural network, ResNet152. Instead of the last layer of ResNet152, we added five additional layers to adopt the model to the present task. All the experiments performed on the popular EmoDB dataset are based on leaving one speaker out of a technique that guarantees the speaker's independency from the model. The model gains an accuracy rate of 88.97% which shows the efficiency of the proposed approach in contrast to other state-of-the-art methods.
کلیدواژه‌های انگلیسی مقاله Wideband and narrowband spectrogram, ResNet152, DCNN, Transfer learning, Speech emotion recognition
نویسندگان مقاله B. Z. Mansouri |
Electrical and Computer Engineering Department, Ferdows branch, Islamic Azad University, Ferdows, Iran.

H.R. Ghaffary |
Electrical and Computer Engineering Department, Ferdows branch, Islamic Azad University, Ferdows, Iran.

A. Harimi |
Electrical and Computer Engineering Department, Ferdows branch, Islamic Azad University, Ferdows, Iran.

نشانی اینترنتی https://jad.shahroodut.ac.ir/article_2576_9ab41e081a2486b986bdbc5e658ee3f4.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات