Abstract: A microphone array position estimation device includes an estimation unit that estimates a position X of a microphone array for maximizing a simultaneous probability P(X,S,Z) of X, Y, and Z through repeated estimation of S and X when the position of the microphone array constituted by M (M is an integer of 1 or greater) microphones is set to X (=(X1T, . . . , XMT)T, T indicates a transposition), spectrums of sound source signals output by the N (N is an integer of 1 or greater) sound sources are set to S (a set related to all of n, f, and t of Snft, f is a frequency bin, and t is a frame index), and spectrums of recorded signals collected by the microphone array are set to Z (a set related to all of f and t of Zft).

Abstract: A sound source localization device includes an acquisition unit configured to acquire acoustic signals of M channels (M is an integer equal to or greater than one), a phase difference information calculator configured to perform a short-time Fourier transform on the acoustic signals of M channels and to convert a time domain into a frequency domain including phase information, and an estimator configured to input phase information of the acoustic signals subjected to the short-time Fourier transform to a deep learning machine and to perform sound source localization of the acoustic signals using the deep learning machine where input follows a von Mises distribution.

Abstract: An acoustic signal processing device includes an acoustic signal processing unit configured to calculate a spectrum of each acoustic signal and a steering vector having m elements on the basis of m acoustic signals converted into m digital signals by sampling m analog signals representing sounds collected by m microphones (m is an integer of 1 or more and M or less, and M is an integer of 2 or more), and to estimate a sampling frequency ?m in the sampling on the basis of the spectrum, the steering vector, and a sampling frequency ?ideal that is a predetermined value.

Abstract: A sound source separating device includes: a signal acquiring unit that acquires the sound signal including mixed sounds from a plurality of sound sources; a start information acquiring unit that acquires start information representing a start timing of at least one sound source among the plurality of sound sources; and a sound source separating unit that separates a specific sound source from the sound signal by setting a binary mask controlling presence of the sound source using a variable of “0” and “1” and using a Markov chain for the activation on the basis of the start information and decomposing the spectrogram generated from the sound signal into the base spectrum and the activation through non-negative matrix factorization using the set binary mask S.

Abstract: A microphone array position estimation device includes an estimation unit that estimates a position X of a microphone array for maximizing a simultaneous probability P(X,S,Z) of X, Y, and Z through repeated estimation of S and X when the position of the microphone array constituted by M (M is an integer of 1 or greater) microphones is set to X (=(X1T, . . . , XMT)T, T indicates a transposition), spectrums of sound source signals output by the N (N is an integer of 1 or greater) sound sources are set to S (a set related to all of n, f, and t of Snft, f is a frequency bin, and t is a frame index), and spectrums of recorded signals collected by the microphone array are set to Z (a set related to all of f and t of Zft).

Abstract: A sound source separating device includes: a signal acquiring unit that acquires the sound signal including mixed sounds from a plurality of sound sources; a start information acquiring unit that acquires start information representing a start timing of at least one sound source among the plurality of sound sources; and a sound source separating unit that separates a specific sound source from the sound signal by setting a binary mask controlling presence of the sound source using a variable of “0” and “1” and using a Markov chain for the activation on the basis of the start information and decomposing the spectrogram generated from the sound signal into the base spectrum and the activation through non-negative matrix factorization using the set binary mask S.

Abstract: A sound source localization device includes an acquisition unit configured to acquire acoustic signals of M channels (M is an integer equal to or greater than one), a phase difference information calculator configured to perform a short-time Fourier transform on the acoustic signals of M channels and to convert a time domain into a frequency domain including phase information, and an estimator configured to input phase information of the acoustic signals subjected to the short-time Fourier transform to a deep learning machine and to perform sound source localization of the acoustic signals using the deep learning machine where input follows a von Mises distribution.

Abstract: An acoustic signal processing device includes an acoustic signal processing unit configured to calculate a spectrum of each acoustic signal and a steering vector having m elements on the basis of m acoustic signals converted into m digital signals by sampling m analog signals representing sounds collected by m microphones (m is an integer of 1 or more and M or less, and M is an integer of 2 or more), and to estimate a sampling frequency ?m in the sampling on the basis of the spectrum, the steering vector, and a sampling frequency ?ideal that is a predetermined value.

Abstract: A system for timbral change, capable of changing timbres included in an existing music audio signal to arbitrary timbres. Replaced harmonic peak parameters are created by replacing a plurality of harmonic peaks included in harmonic peak parameters, which are stored in a separated audio signal analyzing and storing section 3 and indicate relative amplitudes of n-th order harmonic components of each tone generated by a musical instrument of a first kind, with harmonic peaks included in harmonic peak parameters, which are stored in a replacement parameter storing section 6 and indicate relative amplitudes of n-th order harmonic components of each tone generated by a musical instrument of a second kind and corresponding to each tone generated by the musical instrument of the first kind. A synthesized separated audio signal generating section 7 generates a synthesized separated audio signal for each tone using parameters other than the harmonic peak parameters and the replaced harmonic peak parameters.

Abstract: An audio signal produced by playing a plurality of musical instruments is separated into sound sources according to respective instrument sounds. Each time a separation process is performed, the updated model parameter estimation/storage section 114 estimates parameters respectively contained in updated model parameters such that updated power spectrograms gradually change from a state close to initial power spectrograms to a state close to a plurality of power spectrograms most recently stored in a power spectrogram separation/storage section. Respective sections including the power spectrogram separation/storage section 112 and an updated distribution function computation/storage section 118 repeatedly perform process operations until the updated power spectrograms change from the state close to the initial power spectrograms to the state close to the plurality of power spectrograms most recently stored in the power spectrogram separation/storage section 112.

Abstract: A system for timbral change, capable of changing timbres included in an existing music audio signal to arbitrary timbres. Replaced harmonic peak parameters are created by replacing a plurality of harmonic peaks included in harmonic peak parameters, which are stored in a separated audio signal analyzing and storing section 3 and indicate relative amplitudes of n-th order harmonic components of each tone generated by a musical instrument of a first kind, with harmonic peaks included in harmonic peak parameters, which are stored in a replacement parameter storing section 6 and indicate relative amplitudes of n-th order harmonic components of each tone generated by a musical instrument of a second kind and corresponding to each tone generated by the musical instrument of the first kind. A synthesized separated audio signal generating section 7 generates a synthesized separated audio signal for each tone using parameters other than the harmonic peak parameters and the replaced harmonic peak parameters.

Abstract: An audio signal produced by playing a plurality of musical instruments is separated into sound sources according to respective instrument sounds. Each time a separation process is performed, the updated model parameter estimation/storage section 114 estimates parameters respectively contained in updated model parameters such that updated power spectrograms gradually change from a state close to initial power spectrograms to a state close to a plurality of power spectrograms most recently stored in a power spectrogram separation/storage section. Respective sections including the power spectrogram separation/storage section 112 and an updated distribution function computation/storage section 118 repeatedly perform process operations until the updated power spectrograms change from the state close to the initial power spectrograms to the state close to the plurality of power spectrograms most recently stored in the power spectrogram separation/storage section 112.