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Various phonemes are considered in terms of nonlinear dynamics. Phase portraits of the signals in the embedded space, correlation dimension estimate and the largest Lyapunov exponent are analyzed. It is shown that the speech signals have comparatively small dimension and the positive largest Lyapunov exponent
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Citations
A new method is proposed for measurements of an index of acoustic voice quality using the Kulbaka–Leybler information metric. The primary benefit of this method consists in its high-level dynamic properties, as calculated by eliminating the problem of a small number of observational samples. A theoretical study of the method’s efficiency was conducted, and its conclusions were confirmed experimentally. It has been established that, in order to provide a sufficiently precise assessment of the voice quality of the speaker, a speech signal of duration 2–3 minutes is required.
The automatic segmentation of the vocal signal precedes the features extraction stages, respectively the emotion recognition/classification. The extraction of the prosodic parameters as fundamental frequency (F0) and formants (F1-F4) cepstral coefficients LPCC and MFCC are made only on the vowel areas. The analysis tools from the SROL corpus are using a hybrid hierarchical system with four segmentation methods based on the autocorrelation function, AMDF method, the cepstral analysis and HPS method. Since the performance of this instrument has not been yet satisfactory, we analyzed other segmentation possibilities in order to obtain the best possible accuracy in segmentation. The predictive neural network used in this paper is in fact a simple perceptron which can approximate with high accuracy the quasi-periodic signals such as the vowels. The consonants have noisy properties and are complicated transition processes. The prediction error for the consonants comparing with the vowels is higher when it is used a sample neural network architecture.
Speech and music prosody deals with the presence of rhythm. This work is the analysis of the presence of the chaotic nature in the duration patterns of speech segments. A chaotic system is one whose characteristics are apparently random with some amount of predictability. This study is carried out both quantitatively and qualitatively. The qualitative analysis is carried out using recurrence plots and phase space plots, whereas quantitative analysis is carried out using statistical measurements such as Hurst Exponent and Recurrence period density entropy (RPDE). Results obtained in the chaotic analysis are useful in electronic music synthesis and speech synthesis in order to improve the naturality of speech generated.
