Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Macrobenthos And Its Relation To Ecosystem Dynamics In The Cochin Estuary

Cochin estuary is a shallow brackish water body situated on the south west coast of India. It is a tropical positive estuary extending between 90 40’ and 100 12’ N and 760 10’and 760 30’ E with its northern boundary at Azhikode and southern boundary at Thannermukkom bund.The abundance of benthic fauna in an ecosystem shows the close relationship to its environment and reflects the characteristics of an ecological niche. Seasonal and monthly variations in the distribution of macrobenthos in relation to sediment characteristics were conducted in Cochin estuary from 2009-10 periods. Oxidation-reduction potential showed reducing trends that affected the distribution and diversity of fauna. Seasonal variations in water quality and river discharge pattern affected the faunal composition in the different stations. Sewage mixing was the principal source of organic pollution in the Cochin estuary. The sediment pH was generally on the alkaline side ranging from 4.99 at St.9 and 8.33 at St.1.The Eh ranged from -11mV at St.3 to -625mV at St.2.The temperature varied from 260C to 320C in the estuary. The moisture content ranged from 1.63 to 12.155%, that of organic carbon from 0 09 at St. 6 to 4.29% at St.9 and that of organic matter from 0.16 to 7.39%. Seasonally, the average of Eh was highest during the monsoon (156.22 mV) and in the pre monsoon (140.94 mV). The average pH for the 9 study stations was 7.68 during monsoon period and 7.08 during post monsoon. Based on group wise seasonal analysis, the average mean abundance was maximum for polychaetes (43.47) followed by nematodes (33.62), crustaceans (21.62), molluscs (11.94) and Pisces (0.05) in the estuary. Monsoon season was most favourable for benthic faunal abundance followed by the post monsoon period in the study. The series of human interventions like dredging, discharge of industrial effluents, urbanisation and related aspects had a strong influence on the distribution, abundance of benthic macrofauna in the wetland.