17 resultados para low rate speech coding

em Cochin University of Science


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In this paper, the fluorescence behaviour of nano colloids of ZnO has been studied as a function of the excitation wavelength. We have found that excitation at the tail of the absorption band gives rise to an emission that shifts with the change of the excitation wavelength. The excitation wavelength dependent shift of the fluorescence maximum is measured to be between 60 and 100 nm. This kind of excitation wavelength dependent fluorescence behaviour, which may appear to be in violation of Kasha’s rule of excitation wavelength independence of the emission spectrum, has been observed for nano ZnO colloids prepared by two different chemical routes and different capping agents. It is shown that the existence of a distribution of energetically different molecules in the ground state coupled with a low rate of the excited state relaxation processes, namely, solvation and energy transfer, are responsible for the excitation wavelength dependent fluorescence behaviour of the systems.

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In this paper, the fluorescence behaviour of nano colloids of ZnO has been studied as a function of the excitation wavelength. We have found that excitation at the tail of the absorption band gives rise to an emission that shifts with the change of the excitation wavelength. The excitation wavelength dependent shift of the fluorescence maximum is measured to be between 60 and 100 nm. This kind of excitation wavelength dependent fluorescence behaviour, which may appear to be in violation of Kasha’s rule of excitation wavelength independence of the emission spectrum, has been observed for nano ZnO colloids prepared by two different chemical routes and different capping agents. It is shown that the existence of a distribution of energetically different molecules in the ground state coupled with a low rate of the excited state relaxation processes, namely, solvation and energy transfer, are responsible for the excitation wavelength dependent fluorescence behaviour of the systems.

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The work presented in the thesis is centered around two important types of cathode materials, the spinel structured LixMn204 (x =0.8to1.2) and the phospho -oIivine structured LiMP04 (M=Fe and Ni). The spinel system LixMn204, especially LiMn204 corresponding to x= 1 has been extensively investigated to understand its structural electrical and electrochemical properties and to analyse its suitability as a cathode material in rechargeable lithium batteries. However there is no reported work on the thermal and optical properties of this important cathode material. Thermal diffusivity is an important parameter as far as the operation of a rechargeable battery is concerned. In LixMn204, the electronic structure and phenomenon of Jahn-Teller distortion have already been established theoretically and experimentally. Part of the present work is an attempt to use the non-destructive technique (NDT) of photoacoustic spectroscopy to investigate the nature of the various electronic transitions and to unravel the mechanisms leading to the phenomenon of J.T distortion in LixMn204.The phospho-olivines LiMP04 (M=Fe, Ni, Mn, Co etc) are the newly identified, prospective cathode materials offering extremely high stability, quite high theoretical specific capacity, very good cycIability and long life. Inspite of all these advantages, most of the phospho - olivines especially LiFeP04 and LiNiP04 show poor electronic conductivity compared to LixMn204, leading to low rate capacity and energy density. In the present work attempts have been made to improve the electronic conductivity of LiFeP04 and LiNiP04 by adding different weight percentage MWNT .It is expected that the addition of MWNT will enhance the electronic conductivity of LiFeP04 and LiNiP04 with out causing any significant structural distortions, which is important in the working of the lithium ion battery.

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Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.

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This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

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This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

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Zinc salts of ethyl, isopropyl, and butyl xanthates were prepared in the laboratory. The effect of these xanthates in combination with zinc diethyldithiocarbamate (ZDC) on the vulcanization of silica-filled NBR compounds has been studied at different temperatures. The cure times of these compounds were compared with that of NBR compounds containing tetramethylthiuram disulphide/dibenzthiazyl disulphide. The rubber compounds with the xanthates and ZDC were cured at various temperatures from 60 to 150°C. The sheets were molded and properties such as tensile strength, tear strength, crosslink density, elongation at break, compression set, abrasion resistance, flex resistance, heat buildup, etc. were evaluated. The properties showed that zinc salt of xanthate/ZDC combination has a positive synergistic effect on the cure rate and mechanical properties of NBR compounds.

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Zinc salts of ethyl, isopropyl, and butyl xanthates are prepared in the laboratory, and the effect of these xanthates with zinc diethyl dithiocarbamate (ZDC) on the vulcanization of HAF-filled nitrile butadiene rubber (NBR) compounds has been studied at different temperatures. The cure times of these compounds have been compared with that of NBR compounds containing TMTD/MBTS. The rubber compounds with the three xanthate accelerators and ZDC are cured at various temperatures from 60 to 150°C. The sheets are molded and properties such as tensile strength, tear strength, cross-link density, elongation at break, compression set, abrasion resistance, flex resistance, etc. have been evaluated. The properties show that zinc salt of the xanthate/ZDC accelerator system has a positive synergistic effect on the cure rate and mechanical properties of NBR compounds.

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Selected grades of low density polyethylene (LDPE) polystyrene (PS) were extruded in a laboratory extruder by varying the feeding rate at different revolutions per minute and temperatures. The mechanical properties of the extruded plastic sheets were determined. LDPE shows a marked variation in mechanical properties with feeding rate while PS shows a marginal change in mechanical properties with feeding rate. However, for both plastics there is a particular feeding rate in the starved region which results in maximum mechanical properties.

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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.

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LLDPE was blended with poly (vinyl alcohol) and mechanical, thermal, spectroscopic properties and biodegradability were investigated. The biodegradability of LLDPE/PVA blends has been studied in two environments, viz. (1) a culture medium containing Vibrio sp. and (2) a soil environment over a period of 15 weeks. Nanoanatase having photo catalytic activity was synthesized by hydrothermal method using titanium-iso-propoxide. The synthesized TiO2 was characterized by X-Ray diffraction (XRD), BET studies, FTIR studies and scanning electron microscopy (SEM). The crystallite size of titania was calculated to be ≈ 6nm from the XRD results and the surface area was found to be about 310m2/g by BET method. SEM shows that nanoanatase particles prepared by this method are spherical in shape. Linear low density polyethylene films containing polyvinyl alcohol and a pro-oxidant (TiO2 or cobalt stearate with or without vegetable oil) were prepared. The films were then subjected to natural weathering and UV exposure followed by biodegradation in culture medium as well as in soil environment. The degradation was monitored by mechanical property measurements, thermal studies, rate of weight loss, FTIR and SEM studies. Higher weight loss, texture change and greater increments in carbonyl index values were observed in samples containing cobalt stearate and vegetable oil. The present study demonstrates that the combination of LLDPE/PVA blends with (I) nanoanatase/vegetable oil and (ii) cobalt stearate/vegetable oil leads to extensive photodegradation. These samples show substantial degradation when subsequent exposure to Vibrio sp. is made. Thus a combined photodegradation and biodegradation process is a promising step towards obtaining a biodegradable grade of LLDPE.

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Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

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In recent years, reversible logic has emerged as one of the most important approaches for power optimization with its application in low power CMOS, quantum computing and nanotechnology. Low power circuits implemented using reversible logic that provides single error correction – double error detection (SEC-DED) is proposed in this paper. The design is done using a new 4 x 4 reversible gate called ‘HCG’ for implementing hamming error coding and detection circuits. A parity preserving HCG (PPHCG) that preserves the input parity at the output bits is used for achieving fault tolerance for the hamming error coding and detection circuits.

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Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

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While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting