Abstract: An object sound extraction apparatus includes sound source separation sections for separating and generating an object sound separation signal corresponding to an object sound and reference sound separation signals corresponding to the other reference sound based on each combination of a main acoustic signal and sub acoustic signals, an object sound separation signal synthesis section for synthesizing the object sound separation signals, and a spectrum subtraction processing section for extracting an acoustic signal corresponding to the object sound from the synthesis signal by performing a spectrum subtraction processing between the synthesis signal and the reference sound separation signals. Accordingly, in acoustic environments where the object sound and the noises are mixed in the acoustic signals obtained via the microphones, and the mixed conditions can vary, a high object sound extraction performance can be ensured by a small object sound extraction apparatus.

Abstract: To shorten an output delay while a high sound source separation performance is ensured when a sound separation process based on an ICA method is performed. A second Fourier transform process execution cycle t2 for obtaining a second frequency-domain signal S1 used as an input signal of a filter process is set shorter than a first Fourier transform process execution cycle t1 for obtaining a first frequency-domain signal used for a learning computation of a separating matrix. When the time length of a second time-domain signal S1 is set shorter than a time length of a first time-domain signal S0, a second separating matrix used for a filter process is set by aggregating matrix components of a first separating matrix obtained through a learning calculation for every a plurality of groups.

Abstract: A sound source separation apparatus performs a temporary learning processing and a temporary separation processing with respect to each of a plurality of candidate matrixes (separating matrixes obtained by learning calculation based on input signals of different sound source conditions) stored on a candidate matrix memory in advance. The apparatus determines an initial matrix of the separating matrix based on the obtained correlation evaluation of the separated signals. The learning calculations of the initial matrix determination processing and separating matrix based on the initial matrix are performed at a time of the sound source separation processing by the apparatus and when a degree of correlation among the separated signals by a correlation evaluation part exceeds a predetermined level.

Abstract: A sound source separation apparatus includes a first sound source separation unit that performs blind source separation based on independent component analysis to separate a sound source signal from a plurality of mixed sound signals, thereby generating a first separated signal; a second sound source separation unit that performs real-time sound source separation by using a method other than the blind source separation based on independent component analysis to generate a second separated signal; and a multiplexer that selects one of the first separated signal and the second separated signal as an output signal. The first sound source separation unit continues processing regardless of the selection state of the multiplexer. When the first separated signal is selected as an output signal, the number of sequential calculations of a separating matrix performed in the first sound source separation unit is limited to a number that allows for real-time processing.

Abstract: A sound source separation apparatus performs a discrete Fourier transform on each of a plurality of mixed sound signals for a predetermined time length in a time domain and sequentially transforms the mixed sound signals to mixed sound signals in a frequency domain. The apparatus allocates learning calculations of a separating matrix using a blind source separation based on independent component analysis to a plurality of DSPs for each of separate mixed sound signals generated by separating the frequency-domain-based mixed sound signal into a plurality of pieces with respect to frequency range and causes the DSPs to perform the learning calculations in parallel so as to sequentially output the separating matrix. The apparatus generates a separated signal corresponding to the sound source signal from the frequency-domain-based mixed sound signal by performing a matrix calculation using the separating matrix and performs an inverse discrete Fourier transform on the separated signal.