An Improved Approach Of Emotion Recognition Combining Spectral And Prosodic Features With Reference To Assamese Language

نویسنده

  • Akalpita Das
چکیده

In the process of classification of emotions, it is seen that similar emotions always lead to misclassification. Such misclassification need to be reduced by taking an extra measure on performing early classification of those most confusing emotions into some different sub-groups. By grouping acoustically over lapping emotions into separate categories in stage one and classifying individual emotions in stage two. In the current study, “speaking rate” is chosen as the decisive factor for the sub-grouping of acoustically similar emotions. Later both Spectral and prosodic features in combination is used for further classification [1]. In stage one; by using spectral and prosodic features each emotion is categorized in 3 wider groups: 1) active 2) normal, and 3) passive emotions. Such wider groups are made based completely on speaking rate. In stage two, individual emotion sub grouping performed within each wider group. Figure 1.1: Duration of “ ” for emotions a) disgust, b) neutral and c) sarcasm Since it is observed that Excitation source feature has no appreciable influence in speech emotion recognition so it is avoided. We know that speaking rate is only a measure in utterance of number of syllables per unit amount time. It is accepted as most important characteristics for each speaker Abstract: The Speaking rate feature of speech can be explored for discriminating robust emotions. In real life, it is found that certain emotions are used to be very active with high speaking rate while some are very passive with low speaking rate. Keeping this motivation, a Phase II emotion recognition system has been proposed where three broad groups (active, neutral and passive) are taken in Phase I and each broad group are further classified in Phase II. In each stage classification of emotions are done by exploring Spectral and prosodic features. The combination of both spectral and prosodic features found to be performed better.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation

Abstract   Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...

متن کامل

Classification of emotional speech using spectral pattern features

Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...

متن کامل

Combining spectral and prosodic information for emotion recognition in the interspeech 2009 emotion challenge

This paper describes the system presented at the Interspeech 2009 Emotion Challenge. It relies on both spectral and prosodic features in order to automatically detect the emotional state of the speaker. As both kinds of features have very different characteristics, they are treated separately, creating two subclassifiers, one using the spectral features and the other one using the prosodic ones...

متن کامل

An Emotion Recognition Approach based on Wavelet Transform and Second-Order Difference Plot of ECG

Emotion, as a psychophysiological state, plays an important role in human communications and daily life. Emotion studies related to the physiological signals are recently the subject of many researches. In This study a hybrid feature based approach was proposed to examine affective states. To this effect, Electrocardiogram (ECG) signals of 47 students were recorded using pictorial emotion elici...

متن کامل

A 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 کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017