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: The number of conversational tests needed for the evaluation of acoustic quality of the ICC system is reduced. An evaluation value conversion device 3 evaluates the quality of communication between a near-end acoustic region 100 and a far-end acoustic region 200 inside a vehicle for which a plurality of acoustic regions are predetermined. A voice signal picked up by a microphone M2 disposed in the far-end acoustic region 200 is emitted from a speaker S1 disposed in the near-end acoustic region 100.

Abstract: A technique for stably optimizing a variable of model so as to conform the learning data set is provided, even when there is a statistical deviation in a learning data set distributed and accumulated in a plurality of nodes, or communication between nodes is asynchronous and sparse.

Abstract: One aspect of the present invention is a learning device including a self-learning unit that updates content of main conversion processing for converting data to be processed into data in a predetermined format by executing self-supervised learning, and a data augmentation unit that executes data augmentation processing of generating data to be processed in the main conversion processing based on an acoustic time series, in which the data augmentation unit performs acoustic time series clipping processing of clipping a partial time series that is a time series of a part of the acoustic time series, duplication processing of duplicating the partial time series, and conversion processing of converting one and the other of the partial time series according to a predetermined rule, and the self-learning unit updates the content of the main conversion processing by self-supervised learning based on a result obtained by the conversion processing.

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: An autocorrelation calculation unit 21 calculates an autocorrelation RO(i) from an input signal. A prediction coefficient calculation unit 23 performs linear prediction analysis by using a modified autocorrelation R?O(i) obtained by multiplying a coefficient wO(i) by the autocorrelation RO(i). It is assumed here, for each order i of some orders i at least, that the coefficient wO(i) corresponding to the order i is in a monotonically increasing relationship with an increase in a value that is negatively correlated with a fundamental frequency of the input signal of the current frame or a past frame.

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: A threshold acquisition apparatus acquires a threshold for determining whether an anomaly score acquired from a target sound is normal or anomalous. The threshold acquisition apparatus includes: an allowable number setting unit that sets an allowable number of times such that the number of anomaly scores determined to be anomalous included in a set of anomaly scores per predetermined section length, which is a part of time-series acoustic signals that do not include an anomalous sound, does not exceed the allowable number of times; and a threshold estimation unit that estimates a threshold candidate such that the number of sections determined to be anomalous per predetermined section length, which is a part of time-series acoustic signals, satisfies a predetermined criterion by using the allowable number of times, and acquires the threshold candidate as the threshold.

Abstract: An autocorrelation calculation unit 21 calculates an autocorrelation RO(i) from an input signal. A prediction coefficient calculation unit 23 performs linear prediction analysis by using a modified autocorrelation R?O(i) obtained by multiplying a coefficient wO(i) by the autocorrelation RO(i). It is assumed here, for each order i of some orders i at least, that the coefficient wO(i) corresponding to the order i is in a monotonically increasing relationship with an increase in a value that is negatively correlated with a fundamental frequency of the input signal of the current frame or a past frame.

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: 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: 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: An input of a first observation signal corresponding to an incoming signal from a first direction is received, an angular rotation operation of the first observation signal is performed to obtain a second observation signal corresponding to an incoming signal from a second direction that is different from the first direction and the second observation signal is added to a set of training data.

Abstract: An estimation apparatus includes a state estimation unit that estimates a state from an observed amount using an encoder, an observed amount estimation unit that estimates an observed amount from a state using a decoder, and a future observed amount estimation unit that estimates a future observed amount, which is a value to which the observed amount changes with time, using a parameter K representing time evolution, where a parameter of the encoder, a parameter of the decoder, and the parameter K are optimized simultaneously.

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: 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 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: Provided is sound source enhancement technology that is capable of improving sound source enhancement capabilities in 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: 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: 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.