Abstract: An image processing apparatus capable of preventing failure in decoding additional information embedded in a print. The apparatus performs image processing for generating a print in which additional information is embedded. A halftone pattern used for halftone processing is set out of a plurality of halftone patterns. It is determined whether or not, in a case where the set halftone pattern is used for the halftone processing, encoded patterns generated based on the additional information can be uniformly reproduced from a color plane with which the encoded patterns are synthesized. In a case where it is determined that the encoded patterns cannot be uniformly reproduced, a warning notification is performed for notifying before outputting a print in which the additional information is embedded, a user that the print is a print which can cause failure in decoding the additional information.

Abstract: A signal filtering device includes: an information generation unit that generates feature information on related information on a target signal; an extraction unit that extracts mask information from a mixed signal including the target signal on the basis of the feature information; and a mask processing unit that estimates the target signal from the mixed signal using the mask information. The information generation unit may encode the related information into a multidimensional vector and generate a linear transformation result of the multidimensional vector as the feature information. The information generation unit may encode the related information into a first multidimensional vector, encode the mixed signal into a second multidimensional vector, derive a similarity in time series between the first multidimensional vector and the second multidimensional vector, and generate a result of a weighted sum of the similarity in time series and the mixed signal as the feature information.

Abstract: A signal filtering device includes: a separation unit that separates a predetermined number of possibility signals from a mixed signal as possibilities of a target signal; an encoding unit that encodes related information of the target signal into a first feature vector and encodes the predetermined number of possibility signals into the predetermined number of second feature vectors; and a selection unit that derives a similarity between the first feature vector and the second feature vector for each of the possibility signals, and selects a possibility signal of the possibility signals having the highest similarity as the target signal from the predetermined number of possibility signals. The selection unit may derive an inner product of the first feature vector and the second feature vector as the similarity. The predetermined number of possibility signals may be voice signals associated with the predetermined number of sound sources.

Abstract: Voice recognition performance is improved. A voice signal processing method according to an embodiment of the present invention acquires an output value indicating whether to perform voice enhancement on an observation signal in which a voice or noise of another speaker overlaps a voice of a target speaker, or a degree of necessity of performing the voice enhancement. The ratio between the observation signal and the enhancement signal generated by the voice enhancement is decided under a predetermined condition using the acquired output value, and the input signal used for the voice recognition is determined.

Abstract: A signal processing device (10) includes: a speech enhancement unit (11) that generates, from an observation signal, an enhancement signal in which a voice of a speaker is enhanced; an original sound addition unit (12) that adds the observation signal to the enhancement signal; and a speech recognition unit (13) that performs speech recognition on the enhancement signal to which the observation signal is added by the original sound addition unit (12).

Abstract: A program for extending the functionality of general-purpose printing software commonly usable by image forming devices provided by multiple manufacturers allows a user to use a sharpness function. An information processing method for extending functionality of general-purpose printing software commonly usable by image forming devices provided by multiple manufacturers, includes: displaying, on a display unit, a display screen that accepts a setting for sharpness processing; and based on the setting accepted on the display screen, for image data generated by the general-purpose printing software, setting that the sharpness processing be executed by an image forming device to which the image data is sent.

Abstract: An image processing apparatus capable of changing a halftone pattern set to a coding pattern that will be synthesized with an image to another halftone pattern that can uniformly generate the coding pattern when the coding pattern cannot be uniformly generated in performing a halftone process using the halftone pattern set to the cording pattern. A setting unit sets a halftone pattern used in a halftone process from among a plurality of halftone patterns. A determination unit determines whether a coding pattern can be uniformly generated when the halftone process is performed using the halftone pattern set by the setting unit as the coding pattern to be synthesized with an image to be printed. A changing unit changes a halftone pattern used in the halftone process to another halftone pattern capable of uniformly generating the coding pattern when the determination unit determines that the coding pattern cannot be uniformly generated.

Abstract: A voice recognition input determination unit includes SIR-SNR acquisition circuitry that acquires, from a mixed voice in which a voice of another speaker overlaps with a voice of a target speaker, at least one of the mixed voice and a set of a signal-to-interference ratio (SIR) that is a ratio of a target voice to an interference speaker voice in the mixed voice and a signal-to-noise ratio (SNR) that is a ratio of the target voice to a noise in the mixed voice. Further, there is determination circuitry that determines a voice based on at least one of the mixed voice and an enhanced voice obtained by enhancing the mixed voice as a voice to be used for voice recognition on the basis of at least one of the mixed voice and the set of the SIR and the SNR.

Abstract: A signal processing device according to an embodiment of the present invention includes: a conversion unit configured to convert an input mixed acoustic signal into a plurality of first internal states, a weighting unit configured to generate a second internal state which is a weighted sum of the plurality of first internal states based on auxiliary information regarding an acoustic signal of a target sound source when the auxiliary information is input, and generate the second internal state by selecting one of the plurality of first internal states when the auxiliary information is not input, and a mask estimation unit configured to estimate a mask based on the second internal state.

Abstract: An image processing apparatus capable of preventing failure in decoding additional information embedded in a print. The apparatus performs image processing for generating a print in which additional information is embedded. A halftone pattern used for halftone processing is set out of a plurality of halftone patterns. It is determined whether or not, in a case where the set halftone pattern is used for the halftone processing, encoded patterns generated based on the additional information can be uniformly reproduced from a color plane with which the encoded patterns are synthesized. In a case where it is determined that the encoded patterns cannot be uniformly reproduced, a warning notification is performed for notifying before outputting a print in which the additional information is embedded, a user that the print is a print which can cause failure in decoding the additional information.

Abstract: 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.

Abstract: An image processing apparatus capable of changing a halftone pattern set to a coding pattern that will be synthesized with an image to another halftone pattern that can uniformly generate the coding pattern when the coding pattern cannot be uniformly generated in performing a halftone process using the halftone pattern set to the cording pattern. A setting unit sets a halftone pattern used in a halftone process from among a plurality of halftone patterns. A determination unit determines whether a coding pattern can be uniformly generated when the halftone process is performed using the halftone pattern set by the setting unit as the coding pattern to be synthesized with an image to be printed. A changing unit changes a halftone pattern used in the halftone process to another halftone pattern capable of uniformly generating the coding pattern when the determination unit determines that the coding pattern cannot be uniformly generated.

Abstract: A learning device includes a conversion unit, a combination unit, an extraction unit, and an update unit. The conversion unit converts a mixed sound, of which sound sources for each component are known, into embedding vectors for each sound source using an embedding neural network. The combination unit combines the embedding vectors using a combination neural network to obtain a combined vector. The extraction unit extracts a target sound from the mixed sound and the combined vector using an extraction neural network. The update unit updates parameters of the embedding neural network such that a loss function calculated based on information regarding the sound sources for each component of the mixed sound and the target sound extracted by the extraction unit is optimized.

Abstract: 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.

Abstract: An image processing device configured to convert image data of a first resolution into image data of a second resolution higher than the first resolution includes at least one memory, and at least one processor in communication with the at least one memory and configured to cooperate with the at least one memory to calculate a direction and an intensity of an edge from the image data of the first resolution, and determine a pattern for the image data of the second resolution to be replaced by pixels of the image data of the first resolution, based on the direction and the intensity of the edge.

Abstract: 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.

Abstract: An audio signal processing apparatus (10) includes a first auxiliary feature conversion unit (12) and a second auxiliary feature conversion unit (13) that convert a plurality of signals relating to processing of an audio signal of a target speaker into a plurality of auxiliary features for the plurality of signals using a plurality of auxiliary neural networks corresponding to the plurality of signals, and an audio signal processing unit (11) that estimates information regarding an audio signal of the target speaker included in a mixed audio signal using a main neural network based on an input feature of the mixed audio signal and the plurality of auxiliary features, wherein the plurality of signals relating to processing of the audio signal of the target speaker are two or more pieces of information of different modalities.

Abstract: To make it possible to set an appropriate threshold value for detecting a print defect by taking into consideration an impurity included in a sheet. A lower limit value of a threshold value used for detection of a print defect is found and stored in advance. Then, whether or not a threshold value for detecting a print defect, which is set based on user instructions, is an appropriate threshold value is determined by using the lower limit value stored in advance.

Abstract: A signal processing device according to an embodiment of the present invention includes: a conversion unit configured to convert an input mixed acoustic signal into a plurality of first internal states, a weighting unit configured to generate a second internal state which is a weighted sum of the plurality of first internal states based on auxiliary information regarding an acoustic signal of a target sound source when the auxiliary information is input, and generate the second internal state by selecting one of the plurality of first internal states when the auxiliary information is not input, and a mask estimation unit configured to estimate a mask based on the second internal state.

Abstract: A speech recognition system includes a plurality of microphones to receive acoustic signals including speech signals, an input interface to generate multichannel inputs from the acoustic signals, one or more storages to store a multichannel speech recognition network, wherein the multichannel speech recognition network comprises mask estimation networks to generate time-frequency masks from the multichannel inputs, a beamformer network trained to select a reference channel input from the multichannel inputs using the time-frequency masks and generate an enhanced speech dataset based on the reference channel input and an encoder-decoder network trained to transform the enhanced speech dataset into a text. The system further includes one or more processors, using the multichannel speech recognition network in association with the one or more storages, to generate the text from the multichannel inputs, and an output interface to render the text.