Abstract: An envelope sequence is provided that can improve approximation accuracy near peaks caused by the pitch period of an audio signal. A periodic-combined-envelope-sequence generation device according to the present invention takes, as an input audio signal, a time-domain audio digital signal in each frame, which is a predetermined time segment, and generates a periodic combined envelope sequence as an envelope sequence. The periodic-combined-envelope-sequence generation device according to the present invention comprises at least a spectral-envelope-sequence calculating part and a periodic-combined-envelope generating part. The spectral-envelope-sequence calculating part calculates a spectral envelope sequence of the input audio signal on the basis of time-domain linear prediction of the input audio signal.

Abstract: Sound source enhancement technology is provided that is capable of improving sound source enhancement capabilities in accordance with settings of usage and applications. A PSD optimization device includes a PSD updating unit that takes a target sound PSD input value {circumflex over (?)}?S(?, ?), an interference noise PSD input value {circumflex over (?)}?IN(?, ?), and a background noise PSD input value {circumflex over (?)}?BN(?, ?) as input, and generates a target sound PSD output value ?S(?, ?), an interference noise PSD output value {circumflex over (?)}?IN(?, ?), and a background noise PSD output value {circumflex over (?)}?BN(?, ?), by solving an optimization problem for a cost function relating to a variable uS representing a target sound PSD, a variable uIN representing an interference noise PSD, and a variable uBN representing a background noise PSD.

Abstract: Performance of an encoding process and a decoding process for a sound signal is enhanced. A representative value calculating part 110 calculates, for each frequency section by a plurality of samples fewer than the number of frequency samples of a sample sequence of a frequency domain signal corresponding to an input acoustic signal, from the sample sequence of the frequency domain signal, a representative value of the frequency section from sample values of samples included in the frequency section, for each of predetermined time sections. A signal companding part 120 obtains, for each of the predetermined time sections, a frequency domain sample sequence obtained by multiplying a weight according to a function value of the representative value by a companding function for which an inverse function can be defined and each of the samples corresponding to the representative value in the sample sequence of the frequency domain signal, as a sample sequence of a weighted frequency domain signal.

Abstract: Accuracy of unsupervised anomalous sound detection is improved using a small number of pieces of anomalous sound data. A threshold deciding part (13) calculates an anomaly score for each of a plurality of pieces of anomalous sound data, using a normal model learned with normal sound data and an anomaly model expressing the pieces of anomalous sound data, and decides a minimum value among the anomaly scores as a threshold. A weight updating part (14) updates, using a plurality of pieces of normal sound data, the pieces of anomalous sound data and the threshold, weights of the anomaly model so that all the pieces of anomalous sound data are judged as anomalous, and probability of the pieces of normal sound data being judged as anomalous is minimized.

Abstract: To improve accuracy of an evaluation in an acoustic quality evaluation test performed by comparing an evaluation target sound and a reference sound. A data correction apparatus 3 compares, in a call performed between a near-end terminal 1 and a far-end terminal 2, an evaluation target sound in which a voice output from the near-end terminal 1 is recorded and a reference sound in which a voice spoken by a call partner using the far-end terminal 2 to correct test data used in a listening test for evaluating acoustic quality of the call. A correction target determination unit 31 determines, as a correction target section, a voiced section that does not include the voice of the call partner detected from an acoustic signal representing the reference sound. A correction execution unit 32 updates the correction target section of the acoustic signal representing the reference sound with a non-voice signal predetermined.

Abstract: To obtain an appropriate evaluation value in an acoustic quality evaluation by a conversational test. An acoustic quality evaluation apparatus 3 evaluates the acoustic quality of a call performed between a near-end terminal 1 and a far-end terminal 2 via a voice communication network 4. An evaluation value presenting unit 31 displays, on a display unit 13, evaluation categories obtained by classifying each of a plurality of evaluation viewpoints into a predetermined number of levels. An input unit 14 transmits the evaluation category selected by the evaluator for each of the evaluation viewpoints, to an evaluation value determination unit 32. The evaluation value determination unit 32 determines the lowest evaluation value among evaluation values assigned to the evaluation category received from the input unit 14 as a subjective evaluation value for acoustic quality.

Abstract: Provided s sound source enhancement technology that is capable of improving sound source enhancement capabilities a configuration using a beamformer to suppress interference noise. A PSD optimization device includes a PSD updating unit that takes a target sound PSD input value, an interference noise PSD input value, and a background noise PSD input value as input, and generates a target sound PSD output value, an interference noise PSD output value, and a background noise PSD output value, by solving an optimization problem for a cost function relating to a variable representing a target sound PSD, a variable representing an interference noise PSD, and a variable representing a background noise PSD.

Abstract: The number of conversational tests required for evaluation of acoustic quality of the ICC system is reduced. An evaluation value converting device 3 evaluates the quality of a conversation made across a near-end acoustic area 100 and a far-end acoustic area 200 inside a vehicle in which a plurality of acoustic areas are predetermined. A voice signal collected by a microphone M2 disposed in the far-end acoustic area 200 is emitted from a speaker S1 disposed in the near-end acoustic area 100.

Abstract: Provided is an abnormality estimation device capable of appropriately determining normal data appearing less frequently as normal. The abnormality estimation device includes an estimation unit that estimates an anomaly degree of an acoustic signal, by using an abnormality estimation model that is optimized while using a set of normal sounds and is optimized so as to minimize a difference between an anomaly degree of a normal sound appearing more frequently and an anomaly degree of a normal sound appearing less frequently.

Abstract: There is provided a technique for optimizing a latent variable by using a cost function in which a plurality of probabilistic assumptions are reflected simultaneously. A latent variable optimization apparatus includes an optimization unit which optimizes a latent variable ˜w*, vj(1?j?J) is an auxiliary variable of the latent variable ˜w* expressed as vj=Dj˜w*+bj by using a matrix Dj and a vector bj, a cost term of the auxiliary variable vj is expressed by using a probability distribution of the auxiliary variable vj which is log-concave, and the optimization unit optimizes the latent variable ˜w* by solving a minimization problem of a cost function including the sum of the cost term of the auxiliary variable vj.

Abstract: Provided is a non-negative matrix factorization technology of achieving high-speed and stable convergence. A non-negative matrix factorization optimization device includes an optimization unit configured to optimize a non-negative matrix {A, B}, which is factorization of a matrix Z satisfying Z=ABT, by inputting a measurement matrix Y, where Y represents a non-negative measurement matrix representing a measurement signal or measurement data, and Z represents a non-negative matrix constructing the measurement matrix Y, and a cost function J to be used for optimization by the optimization unit is defined by an expression of J(A, B)=G(Y?ABT)+HA(A)+HB(B), where G represents a loss term, HA represents a normalization term for the matrix A, and HB represents a normalization term for the matrix B, and the optimization unit optimizes the matrix {A, B} based on Bregman monotone operator splitting.

Abstract: The accuracy of unsupervised anomalous sound detection is improved. An anomalous sound generation unit 12 generates a pseudo-anomalous sound by associating a sound obtained from a predetermined device with a probability distribution followed by a sound obtained from a desired device group. A threshold value setting unit 13 sets a threshold value so that all anomaly scores calculated from the pseudo-anomalous sound are determined to be anomalous. A parameter update unit 14 uses an obtained normal sound and an obtained anomalous sound, or a threshold value and a value based on the obtained anomalous sound, to update a parameter so to reliably determine an anomalous sound as anomalous and minimize the probability of determining a normal sound as anomalous.

Abstract: Provided is an acoustic signal processing technique for performing a signal transformation suitable for desired signal processing (e.g., sound source enhancement processing) on a signal, and then performing the desired signal processing on the transformed signal. An acoustic signal processing device performs signal processing M which is a desired target on an input acoustic signal x.

Abstract: A howling suppression apparatus includes: an integration processing part that obtains the maximum value among L values corresponding to n-th frames of L i-th signals, for i=1, 2, . . . , L, L being any integer equal to or greater than 2, the L i-th signals being frequency-domain signals obtained from sound signals collected by multiple microphones; and a howling suppression processing part that performs howling suppression processing on at least any of the L i-th signals using the maximum value.

Abstract: An encoder and a decoder are provided that are capable of reproducing a frequency-domain envelope sequence that provides high approximation accuracy around peaks caused by the pitch period of an audio signal by using a small amount of code. An encoder of the present invention comprises a periodic-combined-envelope generating part and a variable-length coding part. The periodic-combined-envelope generating part generates a periodic combined envelope sequence which is a frequency-domain sequence based on a spectral envelope sequence which is a frequency-domain sequence corresponding to a linear predictive coefficient code obtained from an input audio signal and on a frequency-domain period. The variable-length coding part encodes a frequency-domain sequence derived from the input audio signal. A decoder of the present invention comprises a periodic-combined-envelope generating part and a variable-length decoding part.

Abstract: A coding method and a decoding method are provided which can use in combination a predictive coding and decoding method which is a coding and decoding method that can accurately express coefficients which are convertible into linear prediction coefficients with a small code amount and a coding and decoding method that can obtain correctly, by decoding, coefficients which are convertible into linear prediction coefficients of the present frame if a linear prediction coefficient code of the present frame is correctly input to a decoding device.

Abstract: A coding method and a decoding method are provided which can use in combination a predictive coding and decoding method which is a coding and decoding method that can accurately express coefficients which are convertible into linear prediction coefficients with a small code amount and a coding and decoding method that can obtain correctly, by decoding, coefficients which are convertible into linear prediction coefficients of the present frame if a linear prediction coefficient code of the present frame is correctly input to a decoding device.

Abstract: Performance of an encoding process and a decoding process for a sound signal is enhanced. A representative value calculating part 110 calculates, for each frequency section by a plurality of samples fewer than the number of frequency samples of a sample sequence of a frequency domain signal corresponding to an input acoustic signal, from the sample sequence of the frequency domain signal, a representative value of the frequency section from sample values of samples included in the frequency section, for each of predetermined time sections. A signal companding part 120 obtains, for each of the predetermined time sections, a frequency domain sample sequence obtained by multiplying a weight according to a function value of the representative value by a companding function for which an inverse function can be defined and each of the samples corresponding to the representative value in the sample sequence of the frequency domain signal, as a sample sequence of a weighted frequency domain signal.

Abstract: A possible region of encoding results of anomalous samples is limited. An encoder storage unit 14 stores an encoder for projecting an input feature value into a latent space in which the latent space is a closed manifold, a normal distribution obtained by learning normal data and an anomalous distribution obtained by learning anomalous data are held on the manifold, and a decoder for reconstructing the output of the encoder. An encoding unit 15 obtains a reconstruction result output by the decoder when a feature value of target data is input to the encoder. An anomaly score calculation unit 16 calculates an anomaly score of the target data based on distances between the reconstruction result and the normal distribution and distances between the reconstruction result and the anomalous distribution.

Abstract: An anomaly detection technique which realizes high accuracy while reducing cost required for normal model learning is provided. An anomaly detection apparatus includes an anomaly degree estimating unit configured to estimate an anomaly degree indicating a degree of anomaly of anomaly detection target equipment from sound emitted from the anomaly detection target equipment (hereinafter, referred to as anomaly detection target sound) based on association between a first probability distribution indicating distribution of normal sound emitted from one or more pieces of equipment different from the anomaly detection target equipment and normal sound emitted from the anomaly detection target equipment (hereinafter, referred to as normal sound for adaptive learning).