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公开(公告)号:US20230370778A1
公开(公告)日:2023-11-16
申请号:US18030981
申请日:2020-10-15
IPC分类号: H04R5/04 , H04R3/04 , G10L21/0208 , G10L21/0272
CPC分类号: H04R5/04 , H04R3/04 , G10L21/0208 , G10L21/0272 , G10L2021/02082
摘要: Provided is an acoustic signal enhancement device, including
a time-space covariance matrix estimation unit 2 configured to estimate a time-space covariance matrix Rf(n),Pf(n) corresponding to a sound source n, using a power λt,f(n) of the sound source n and an observation signal vector Xt,f composed of an observation signal xm,t,f from a microphone m;
a reverberation suppression unit 3 configured to obtain a reverberation removal filter Gf(n) of the sound source n using the time-space covariance matrix Rf(n),Pf(n), and to generate a reverberation suppression signal vector Zt,f(n) corresponding to the observation signal xm,t,f for an emphasized sound of the sound source n using the reverberation removal filter Gf(n) and the observation signal vector Xt,f; and
a sound source separation unit 4 configured to obtain an emphatic sound yt,f(n) of the sound source n and the power λt,f(n) of the sound source n using the reverberation suppression signal vector Zt,f(n).-
公开(公告)号:US20240129666A1
公开(公告)日:2024-04-18
申请号:US18273272
申请日:2021-01-29
发明人: Tsubasa OCHIAI , Marc DELCROIX , Tomohiro NAKATANI , Rintaro IKESHITA , Keisuke KINOSHITA , Shoko ARAKI
摘要: An estimation apparatus 10 is a signal processing apparatus for processing an acoustic signal and estimates an observation signal of a virtual microphone arranged virtually from an input observation signal of a real microphone using a deep learning model having a neural network (NN) 11.
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公开(公告)号:US20240038254A1
公开(公告)日:2024-02-01
申请号:US18020084
申请日:2020-08-13
发明人: Tsubasa OCHIAI , Marc DELCROIX , Yuma KOIZUMI , Hiroaki ITO , Keisuke KINOSHITA , Shoko ARAKI
IPC分类号: G10L21/028 , G10L25/30
CPC分类号: G10L21/028 , G10L25/30
摘要: A signal processing device includes processing circuitry configured to receive an input of extraction target information indicating which audio class of an audio signal is to be extracted from a mixture audio signal constituted by a mixture of audio signals of a plurality of audio classes, and output a result of extracting the audio signal of the audio class indicated by the extraction target information from the mixture audio signal, with a neural network by using a feature value of the mixture audio signal and the extraction target information.
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公开(公告)号:US20240038253A1
公开(公告)日:2024-02-01
申请号:US18265909
申请日:2020-12-14
发明人: Rintaro IKESHITA , Tomohiro NAKATANI , Shoko ARAKI
IPC分类号: G10L21/0216 , G06F17/11 , G06F17/16
CPC分类号: G10L21/0216 , G06F17/11 , G06F17/16
摘要: A sound source signal generation technology based on an optimization algorithm that enables high-speed processing of sound source extraction is provided. A sound source signal generation device includes an optimization unit that optimizes a separation matrix W(f)=[w1(f), . . . , wK(f), WZ(f)] using an observed signal x(f, t), the optimization unit includes an auxiliary function calculation unit that calculates an auxiliary function Vi(f) (i=1, . . . , K) according to a predetermined equation, a first separation filter calculation unit that calculates a separation filters wi(f) (i=1, . . . , K) using auxiliary functions Vi(f) (i=1, . . . , K) and Vz(f), and a second separation filter calculation unit that calculates a separation filter WZ(f) according to a predetermined equation when a convergence condition is satisfied.
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公开(公告)号:US20240312446A1
公开(公告)日:2024-09-19
申请号:US18571765
申请日:2021-09-30
发明人: Tomohiro NAKATANI , Rintaro IKESHITA , Keisuke KINOSHITA , Hiroshi SAWADA , Naoyuki KAMO , Shoko ARAKI
IPC分类号: G10K11/178 , H04R3/00
CPC分类号: G10K11/17821 , G10K11/17881 , H04R3/005
摘要: There is provided an acoustic signal enhancement device that receives, as an input, a recording sound obtained by frequency division and updates parameters, the device including: assuming that a switch weight is a weight indicating a ratio of a classification to which a recording sound at each timing belongs in classifications of spatial states where a recording sound temporally changes, a beamformer unit that performs beamformer processing based on a weighted spatial covariance matrix which is updated and updates an auxiliary estimation value of a target sound; a switch unit that updates the switch weight and power of a target sound based on the updated auxiliary estimation value and outputs an estimation value of the target sound; and a weighted spatial covariance estimation unit that updates the weighted spatial covariance matrix based on the updated switch weight and the power.
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公开(公告)号:US20220130406A1
公开(公告)日:2022-04-28
申请号:US17437701
申请日:2020-02-28
发明人: Tomohiro NAKATANI , Marc DELCROIX , Keisuke KINOSHITA , Shoko ARAKI , Yuki KUBO
IPC分类号: G10L21/0232 , G10L21/028 , G10K11/175
摘要: A time-variant noise spatial covariance matrix is estimated effectively. Using time-frequency-divided observation signals based on observation signals acquired by collecting acoustic signals emitted from one or a plurality of sound sources and mask information expressing the occupancy probability of a component of each of the time-frequency-divided observation signals that corresponds to each noise source, a time-independent first noise spatial covariance matrix corresponding to the time-frequency-divided observation signals and the mask information belonging to a long time interval is acquired for each noise source. Further, using the mask information of each of a plurality of different short time intervals, a mixture weight corresponding to each noise source in each short time interval is acquired. Furthermore, a time-variant third noise spatial covariance matrix is acquired, the third noise spatial covariance matrix being based on a time-variant second noise spatial covariance matrix, which corresponds to the time-frequency-divided observation signals and the mask information belonging to each short time interval and relates to noise formed by adding together all of the noise sources, and a weighted sum of the first noise spatial covariance matrices with the mixture weights of the respective short time intervals.
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公开(公告)号:US20180366135A1
公开(公告)日:2018-12-20
申请号:US15779926
申请日:2016-12-01
IPC分类号: G10L21/0232 , G10L21/0308
摘要: An observation feature value vector is calculated based on observation signals recorded at different positions in a situation in which target sound sources and background noise are present in a mixed manner; masks associated with the target sound sources and a mask associated with the background noise are estimated; a spatial correlation matrix of the target sound sources that includes the background noise is calculated based on the masks associated with the observation signals and the target sound sources; a spatial correlation matrix of the background noise is calculated based on the masks associated with the observation signals and the background noise; and a spatial correlation matrix of the target sound sources is estimated based on the matrix obtained by weighting each of the spatial correlation matrices by predetermined coefficients.
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公开(公告)号:US20230087982A1
公开(公告)日:2023-03-23
申请号:US17802090
申请日:2020-02-26
发明人: Rintaro IKESHITA , Tomohiro NAKATANI , Shoko ARAKI
IPC分类号: G10L21/028 , G10L25/21 , G10L21/0224
摘要: A signal processing device applies a convolutional separation filter, which is a combined filter of: a rear reverberation removal filter for suppressing a rear reverberation component from a mixed acoustic signal obtained by converting an observed mixed acoustic signal obtained by observing a source signal into a time-frequency domain; and a sound source separation filter for emphasizing components corresponding to source signals from the mixed acoustic signal, to a mixed acoustic signal string including the mixed acoustic signal and a delay signal of the mixed acoustic signal and estimates model parameters of a model for obtaining information corresponding to signals in which the rear reverberation component is suppressed and target signals emitted from target sound sources in the source signal are emphasized.
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公开(公告)号:US20230067132A1
公开(公告)日:2023-03-02
申请号:US17794266
申请日:2020-02-14
发明人: Tsubasa OCHIAI , Marc DELCROIX , Rintaro IKESHITA , Keisuke KINOSHITA , Tomohiro NAKATANI , Shoko ARAKI
IPC分类号: G10L21/0272 , H04R3/00 , G10L25/93
摘要: A signal processing apparatus includes a neural network (“NN”), a sorting unit, and a spatial covariance matrix calculation unit. The NN converts a mixed signal, in which sounds of a plurality of sound sources input by a plurality of channels are mixed, into a separated signal separated into a signal for each sound source as a signal in a time domain as it is and outputs the separated signal. The sorting unit sorts, for the separated signal of each channel output from the NN, the separated signal of each channel such that the plurality of sound sources of a plurality of the separated signals are aligned among the plurality of channels. The spatial covariance matrix calculation unit calculates a spatial covariance matrix corresponding to each sound source in accordance with the separated signal for each channel output from the sorting unit and sorted.
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公开(公告)号:US20190267019A1
公开(公告)日:2019-08-29
申请号:US15998742
申请日:2016-12-20
发明人: Nobutaka ITO , Shoko ARAKI , Tomohiro NAKATANI
IPC分类号: G10L21/028 , G10L21/0308 , G06K9/62
摘要: A feature extraction unit in a mask estimation apparatus extracts, from a plurality of observation signals obtained by observing a plurality of acoustic signals at different positions, feature vectors obtained by collecting time-frequency components of the observation signals for each time-frequency point. A mask update unit uses the feature vectors, a mixture weight of each component distribution, and a shape parameter that is a model parameter capable of controlling a shape of each component distribution, where a probability distribution of the feature vectors is modeled by a mixture distribution consisting of a plurality of component distributions, to estimate masks indicating a proportion in which each component distribution contributes to each time-frequency point. A mixture weight update unit updates the mixture weight based on the updated masks. A parameter update unit updates the shape parameter by using the feature vectors and the masks.
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