Evolutionary cepstral coefficients

Improving 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...

Speech 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...

Fuzzy decision fusion of complementary experts based on evolutionary cepstral coefficients for phoneme recognition

Acoustic Emotion Recognition Using Linear and Nonlinear Cepstral Coefficients

Recognizing human emotions through vocal channel has gained increased attention recently. In this paper, we study how used features, and classifiers impact recognition accuracy of emotions present in speech. Four emotional states are considered for classification of emotions from speech in this work. For this aim, features are extracted from audio characteristics of emotional speech using Linea...

Age and gender classification using modulation cepstrum

This paper proposes using modulation cepstrum coefficients instead of cepstral coefficients for extracting metadata information such as age and gender. These coefficients are extracted by applying discrete cosine transform to a time-sequence of cepstral coefficients. Lower order coefficients of this transformation represent smooth cepstral trajectories over time. Results presented in this paper...

Noise-Robust Speech Features Based on Cepstral Time Coefficients

In this paper, we investigate the noise-robustness of features based on the cepstral time coefficients (CTC). By cepstral time coefficients, we mean the coefficients obtained from applying the discrete cosine transform to the commonly used mel-frequency cepstral coefficients (MFCC). Furthermore, we apply temporal filters used for computing delta and acceleration dynamic features to the CTC, res...