ABSTRACT
This project presents a novel voice verification system using wavelet transforms. The conventional signal processing techniques assume the signal to be stationary and are ineffective in recognizing non stationary signals such as the voice signals. Voice signals which are more dynamic could be analyzed with far better accuracy using wavelet transform. The developed voice recognition system is word dependant voice verification system combining the RASTA and LPC. The voice signal is filtered using the special purpose voice signal filter using the Relative Spectral Algorithm (RASTA). The signals are denoised and decomposed to derive the wavelet coefficients and thereby a statistical computation is carried out. Further the formant or the resonance of the voices signal is detected using the Linear Predictive Coding (LPC). With the statistical computation on the coefficients alone, the accuracy of the verifying sample individual voice to his own voice is quite high (around 75% to 80%). The reliability of the signal verification is strengthened by combining entailments from these two completely different aspects of the individual voice. For voice comparison purposes four out five individuals are verified and the results show higher percentage of accuracy. The accuracy of the system can be improved by incorporating advanced pattern recognition techniques such as Hidden Markov Model (HMM)
Speech is a very basic way for humans to convey information to one another. With a bandwidth of only 4 kHz, speech can convey information with the emotion of a human voice. People want to be able to hear someone’s voice from anywhere in the world. As if the person was in the same room. As a result a greater emphasis is being placed on the design of new and efficient speech coders for voice communication and transmission.
Today applications of speech coding and compression have become very numerous. Many applications involve the real time coding of speech signals, for use in mobile satellite communications, cellular telephony, and audio for videophones or video teleconferencing systems. Other applications include the storage of speech for speech synthesis and playback, or for the transmission of voice at a later time. Some examples include voice mail systems, voice memo wristwatches, voice logging recorders and interactive PC software. Traditionally speech coders can be classified into two categories: waveform coders and analysis/synthesis vocoders (from .voice coders.). Waveform coders attempt to copy the actual shape of the signal produced by the microphone and its associated analogue circuits
A popular waveform coding technique is pulse code modulation (PCM), This is used in telephony today. Vocoders use an entirely different approach to speech coding, known as parameter coding, or analysis/synthesis coding where no attempt is made at reproducing the exact speech waveform at the receiver, only a signal perceptually equivalent to it. These systems provide much lower data rates by using a functional model of the human speaking mechanism at the receiver. One of the most popular techniques for analysis synthesis coding of speech is called Linear Predictive Coding (LPC). Some higher quality vocoders include RELP (Residual Excited Linear Prediction) and CELP (Code Excited Linear Prediction)