D. Pravena

Development of simulated emotion speech database for excitation source analysis

The work presented in this paper is focused on the development of a simulated emotion database particularly for the excitation source analysis. The presence of simultaneous electroglottogram (EGG) recordings for each emotion utterance helps to accurately analyze the variations in the source parameters according to different emotions. The work presented in this paper describes the development of comparatively large simulated emotion database for three emotions (Anger, Happy and Sad) along with neutrally spoken utterances in three languages (Tamil, Malayalam and Indian English). Emotion utterances in each language are recorded from 10 speakers in multiple sessions (Tamil and Malayalam). Unlike the existing simulated emotion databases, instead of emotionally neutral utterances, emotionally biased utterances are used for recording. Based on the emotion recognition experiments, the emotions elicited from emotionally biased utterances are found to show more emotion discrimination as compared to emotionally neutral utterances. Also, based on the comparative experimental analysis, the speech and EGG utterances of the proposed simulated emotion database are found to preserve the general trend in the excitation source characteristics (instantaneous F0 and strength of excitation parameters) for different emotions as that of the classical German emotion speech-EGG database (EmoDb). Finally, the emotion recognition rates obtained for the proposed speech-EGG emotion database using the conventional mel frequency cepstral coefficients and Gaussian mixture model based emotion recognition system, are found to be comparable with that of the existing German (EmoDb) and IITKGP-SESC Telugu speech emotion databases.

Effectiveness of polarity detection for improved epoch extraction from speech

The objective of the present work is to demonstrate the significance of speech polarity detection in improving the accuracy of the estimated epochs in speech. The paper also proposes a method to extract the speech polarity information using the properties of the Hilbert transform. The Hilbert transform of the speech is computed as the imaginary part of the complex analytic signal representation of the original speech. The Hilbert envelope (HE) is then computed as the magnitude of the analytic signal. The average slope of the signal amplitudes of speech and Hilbert transform of speech around the peaks in the HE are observed to be varying in accordance with the polarity of the speech signal. The effectiveness of the proposed approach is confirmed by the performance evaluation over 7 voices of the phonetically balanced CMU-Arctic database and German emotional speech database. The performance of the proposed approach is also observed to be comparable with that of the existing algorithms such as residual skewness based polarity detection and Hilbert phase based speech polarity detection. Finally, a significant improvement in the identification accuracies of the estimated epochs in speech using the popular zero frequency filtering (ZFF) method is demonstrated as an application of the speech polarity detection.

Improved method for epoch estimation in telephonic speech signals using zero frequency filtering

Epochs are the locations correspond to glottal closure instants for voiced speech segments and onset of bursts or frication in unvoiced segments. In the recent years, the zero frequency filtering (ZFF) based epoch estimation has received a growing attention for clean or studio speech signals. The ZFF based epoch estimation exploits the impulse like excitation characteristics at the zero frequency (DC) region in speech. As the lower frequency regions in telephonic speech are significantly attenuated, ZFF approach gives degraded epoch estimation performance. Therefore, the objective of the present work is to propose refinements to the existing ZFF based epoch estimation algorithm for improved epoch estimation in telephonic speech. The strength of the impulses at the zero frequency region are enhanced by computing the Hilbert envelope (HE) of the speech which in turn improve the epoch estimation performance. The resonators located at the approximate F0 locations of the short term blocks of conventional zero frequency filtered signal, are also found to improve the epoch estimation performance in telephonic speech. The performance of the refined ZFF method is evaluated on 3 speaker voices (JMK, SLT and BDL) of CMU Arctic database having simultaneous speech and EGG recordings. The telephonic version of CMU Arctic database is simulated using tools provided by the international telecommunication union (ITU).

Significance of incorporating excitation source parameters for improved emotion recognition from speech and electroglottographic signals

The work presented in this paper explores the effectiveness of incorporating the excitation source parameters such as strength of excitation and instantaneous fundamental frequency (

Significance of exploring pitch only features for the recognition of spontaneous emotions from speech signals

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Identifying Issues in Estimating Parameters from Speech Under Lombard Effect

F0) for emotion recognition task from speech and electroglottographic (EGG) signals. The strength of excitation (SoE) is an important parameter indicating the pressure with which glottis closes at the glottal closure instants (GCIs). The SoE is computed by the popular zero frequency filtering (ZFF) method which accurately estimates the glottal signal characteristics by attenuating or removing the high frequency vocaltract interactions in speech. The arbitrary impulse sequence, obtained from the estimated GCIs, is used to derive the instantaneous

Improved Phone Recognition Using Excitation Source Features

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