CMAC for speech emotion profiling
نویسندگان
چکیده
Cultural differences have been one of the many factors that can cause failures in speech emotion analysis. If this cultural parameter could be regarded as noise artifacts in detecting emotion in speech, we could then extract pure emotion speech signal from the raw emotional speech. In this paper we use the amplitude spectral subtraction (ASS) method to profile the emotion from raw emotional speech based on the affection space model. In addition, the robustness of the cerebellar model arithmetic computer (CMAC) is used to ensure that all other noise artifacts can be suppressed. Result from the speech emotion profiling shows potential of such technique to visualize hidden features for detecting intracultural and inter-cultural variation that is missing from current approach of speech emotion recognition.
منابع مشابه
語音增強基於小腦模型控制器(A Speech Enhancement System Based on Cerebellar Model Articulation Controller) [In Chinese]
Traditionally, cerebellar model articulation controller (CMAC) is used in motor control, inverted pendulum robot, and nonlinear channel equalization. In this study, we investigate the capability of CMAC for speech enhancement. We construct a CMAC-based supervised speech enhancement system, which includes offline and online phases. In the offline phase, a paired noisy-clean speech dataset is pre...
متن کاملA 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 کاملSpeech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions
Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC) in a speech emotion recognition system. We investigate its perfor...
متن کاملImproving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...
متن کاملClassification 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