Characteristics Of Human Speech Research Articles

Solution of the Problem of Classification of Hydroacoustic Signals Based on Harmonious Wavelets and Machine Learning

Two types of real hydroacoustic signals of whales are classified based on the harmonic wavelet transform (HWT) coefficients (fast implementation), windowed Fourier transform (FT) (spectrogram), and conventional FT using the k-NN algorithm. The accuracy of the classification is estimated for various signal-to-noise ratios (SNRs). In order to reduce the dimension of the feature space during classification using the k-NN algorithm, the use of the modulo N reduction method is proposed. The efficiency of the use of harmonic wavelets in the classification of complex nonstationary signals is experimentally proved. The applicability of speech processing methods for the classification of underwater bioacoustic signals is confirmed. The discussed methods are initially developed taking into account the characteristics of human speech, but, nevertheless, showed good results even without being tuned to the characteristics of the classified signals. The problem of classifying two types of whales by the sounds they make using a neural network is solved.

Integration of harmonic and analysis by synthesis coders

Hybrid coding of speech has been proposed to overcome the limitations of a single model in representing the wide variety of characteristics of human speech. A new hybrid coding algorithm, which combines harmonic and analysis by synthesis coding techniques, is presented. To integrate the harmonic and analysis by synthesis coders, novel phase synchronisation and speech classification techniques are developed. The perceptual quality of the speech synthesised using the unquantised hybrid model is almost indistinguishable when compared with 128 kbit/s linear PCM. Two variable rate coders are developed based on the designed hybrid model, by quantising the parameters at different bit rates. Subjective listening tests show that the speech quality of the variable rate hybrid coders outperform the quality of 5.3 kbit/s and 6.3 kbit/s ITU G.723.1 coders, at maximum bit rates of 4 kbit/s and 6 kbit/s respectively.