Speech Emotion Recognition using Support Vector Machine
نویسندگان
چکیده
منابع مشابه
Speech Emotion Recognition Using Support Vector Machine
Speech Emotion Recognition (SER) is a hot research topic in the field of Human Computer Interaction (HCI). In this paper, we recognize three emotional states: happy, sad and neutral. The explored features include: energy, pitch, linear predictive spectrum coding (LPCC), mel-frequency spectrum coefficients (MFCC), and mel-energy spectrum dynamic coefficients (MEDC). A German Corpus (Berlin Datab...
متن کاملA hybrid EEG-based emotion recognition approach using Wavelet Convolutional Neural Networks (WCNN) and support vector machine
Nowadays, deep learning and convolutional neural networks (CNNs) have become widespread tools in many biomedical engineering studies. CNN is an end-to-end tool which makes processing procedure integrated, but in some situations, this processing tool requires to be fused with machine learning methods to be more accurate. In this paper, a hybrid approach based on deep features extracted from Wave...
متن کاملSupport Super-Vector Machines in Automatic Speech Emotion Recognition
In this paper, we use super-vectors in support vector machines for automatic speech emotion recognition. In our implementation, an utterance is converted to a super-vector formed by the mean vectors of a Gaussian mixture model adapted from a universal background model. The proposed method is evaluated on FAU-Aibo database which is wellknown to be used in INTERSPEECH 2009 Emotion Challenge. In t...
متن کاملA hierarchical support vector machine based on feature-driven method for speech emotion recognition
Through the analysis of one-vs.-one, one-vs.-rest and the decision tree mechanism of binary support vector machine emotion classifiers, a method based on feature-driven hierarchical support vector machine is proposed for speech emotion recognition. For each layer, classifier used different feature parameters to drive its performance, and each emotion is subdivided layer by layer. This method di...
متن کاملP65: Speech Recognition Based on Bbrain Signals by the Quantum Support Vector Machine for Inflammatory Patient ALS
People communicate with each other by exchanging verbal and visual expressions. However, paralyzed patients with various neurological diseases such as amyotrophic lateral sclerosis and cerebral ischemia have difficulties in daily communications because they cannot control their body voluntarily. In this context, brain-computer interface (BCI) has been studied as a tool of communication for thes...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2010
ISSN: 0975-8887
DOI: 10.5120/431-636