Abstract: A composite finite impulse response digital filter for use in an image processing apparatus or the like includes a plurality of sub-filters connected in series. In each sub-filter, a random access memory (RAM) is provided for storing an input data and a barrel shifter is provided for shifting the data to a least significant bit (LSB) or most significant bit (MSB) side over the number of shifts corresponding to a first control signal. Because of the provision of the barrel shifter in each sub-circuit, it is not necessary to shift a data input into an input terminal over a predetermined number of bits before storing into the RAM. Thus, the memory capacity of the RAM can be significantly reduced in size.

Abstract: A noise suppression apparatus has a main microphone for mainly picking up a voice and for outputting an input signal including an audio signal and a first noise component generated from a noise source, a reference microphone for picking up a second noise component generated from the noise source, a filter bank for band-dividing the input signal from the main microphone and the second noise component from the reference microphone, and a noise cancel circuit for obtaining a phase difference between the input signal and the second noise component with respect to each divided band of the filter bank so as to correct the input signal based on the phase difference and for cancelling the first noise component in the input signal by use of the corrected input signal.

Abstract: A voice pattern in the form of a matrix and comprised of a plurality of frames, each including time-spectral information and temporal information, is formed from an unknown input voice signal. The voice pattern is compared with each of the voice patterns of a library of known voices partly to select a plurality of candidate voices. Each of the library voices has a predetermined eigenvector and an inner product frequency distribution of inner products between the eigenvector and the frames of its voice pattern. Then, inner products between the voice pattern of the input voice signal and the eigenvector of each of the candidate library voice are calculated. One of the plurality of candidate library voices whose predetermined inner product frequency distribution is most similar to one of the thus calculated inner product frequency distributions is selected to identify the input voice signal.

Abstract: A voice spectrum analyzing method and system subjects a voice signal to frequency analysis by passing the voice signal through a filter bank containing a plurality of band pass filters each having a different band pass filter range to produce a voice spectral pattern over a predetermined frequency range. The voice spectral pattern is sampled at a predetermined sampling time interval successively, and each of the sampled voice spectral patterns is stored for a predetermined time period. While the voice spectral pattern is retained, it is scanned once in a predetermined time sequence, thereby forming an approximate periodic signal from a series of the scanned voice spectral voice patterns. And the periodic signal thus formed is then digitized and filtered through a digital high pass filter, thereby obtaining a high frequency component from the periodic signal which indicates a feature parameter of the voice signal.

Abstract: A frequency spectral distribution of sound signal has a plurality of discrete data at respective channels where sampling takes place. Such a spectral distribution, defining a parallel signal, is converted into a time series signal which is used to produce a peak-detected signal and a zero-cross signal. Then, based on the timing of the zero-cross signal, the peak-detected signal is compared with the original parallel signal to process the original parallel signal to be binary-valued. The present invention provides a simple hardware structure having the above-described function.