Kabushiki Kaisha Toshiba

Makoto Hirohata

Masashi Nishiyama

Kazunori Imoto

Hisashi Aoki

Toru Taniguchi

Tomoyuki Shibata

Yusuke Kida

Ning Ding

Taro Masuda

Koji Yamamoto

Toshiyuki Ono

Masahiro Sekine

Yoshihiro Ohmori

Kaoru Sugita

Tatsuya Uehara

Shihomi Takahashi

According to an embodiment, a speech processing device includes an extractor, a classifier, a similarity calculator, and an identifier. The extractor is configured to extract a speech feature from utterance data. The classifier is configured to classify the utterance data into a set of utterances for each speaker based on the extracted speech feature. The similarity calculator is configured to calculate a similarity between the speech feature of the utterance data included in the set and each of a plurality of speaker models. The identifier is configured to identify a speaker for each set based on the calculated similarity.

Speech processing device, speech processing method, and computer program product

According to one embodiment, a signal processing apparatus includes a memory and a processor electrically coupled to the memory. The processor separates a plurality of signals by a separation filter, and outputs a plurality of separate signals. The plurality of signals includes signals which are received at different positions and come from different directions. The processor estimates incoming directions of the plurality of separate signals, respectively, and associates the plurality of separate signals with transmission sources of the signals, and present association between the plurality of separate signals and the transmission sources of the signals.

Signal processing apparatus, signal processing method and audio association presentation apparatus

According to one embodiment, a signal processing apparatus includes a processer. The processor separates a plurality of signals, which are received at different positions and come from different directions, by a separation filter. The processor estimates incoming directions of a plurality of separate signals respectively, and associates the plurality of separate signals with transmission sources of the plurality of signals. The processor associates either one of a first attribute and a second attribute with the separate signals which are associated with the transmission sources of the signals based on results of the estimation of the incoming directions in a first period, and add either one of first label information and second label information.

Signal processing apparatus, signal processing method and labeling apparatus

A noise suppression device includes an estimating unit that estimates, from a feature quantity representing the feature in each frequency range of a first acoustic signal which represents sound, the noise component of the feature quantity; a calculating unit that calculates, from the feature quantity and the noise component for each frequency range, a first suppression coefficient to be used in suppressing noise included in the first acoustic signal; a first attenuating unit that attenuates the first suppression coefficient in the time domain and calculates a second suppression coefficient; a second attenuating unit that attenuates the second suppression coefficient in the frequency domain and calculates a third suppression coefficient; and a generating unit that estimates, from the feature quantity and the third suppression coefficient, a voice component of the feature quantity and generates a second acoustic signal in which the noise included in the first acoustic signal is suppressed.

Noise suppression device, noise suppression method, and computer program product

According to an embodiment, a signal processing apparatus includes an ambient sound estimating unit, a representative component estimating unit, a voice estimating unit, and a filter generating unit. The ambient sound estimating unit is configured to estimate, from the feature, an ambient sound component that is non-stationary among ambient sound components having a feature. The representative component estimating unit is configured to estimate a representative component representing ambient sound components estimated from one or more features for a time period, based on a largest value among the ambient sound components within the time period. The voice estimating unit is configured to estimate, from the feature, a voice component having the feature. The filter generating unit is configured to generate a filter for extracting a voice component and an ambient sound component from the feature, based on the voice component and the representative component.

Signal processing apparatus, signal processing method and computer program product for separating acoustic signals

In a speech processing apparatus, an acquisition unit is configured to acquire a speech. A separation unit is configured to separate the speech into a plurality of sections in accordance with a prescribed rule. A calculation unit is configured to calculate a degree of similarity in each combination of the sections. An estimation unit is configured to estimate, with respect to the each section, a direction of arrival of the speech. A correction unit is configured to group the sections whose directions of arrival are mutually similar into a same group and correct the degree of similarity with respect to the combination of the sections in the same group. A clustering unit is configured to cluster the sections by using the corrected degree of similarity.

Speech processing apparatus and method

According to an embodiment, a signal processing device includes a background calculator, a signal generator, an extractor, a similarity calculator, and a mixer. The background calculator is configured to calculate a first background signal in which a speech signal is removed, based on the acoustic signals. The signal generator is configured to generate a reference signal from at least one of the acoustic signals. The extractor is configured to extract a second background signal by removing a speech signal from the reference signal. The similarity calculator is configured to calculate a similarity between feature data of the background signals. The mixer is configured to calculate a weighted sum of the background signals in such a way that a greater weight is given to the first background signal as the similarity is higher and a greater weight is given to the second background signal as the similarity is lower.

Signal processing device, signal processing method, and computer program product

In an embodiment, an image processing device includes: a first calculating unit; a selecting unit; an extracting unit; a second calculating unit; a determining unit; and a generating unit. The first calculating unit calculates posture information of a subject from a first image including the subject. The selecting unit selects a second image associated with the posture information from a plurality of second images including clothing. The extracting unit extracts a first feature of the subject from a first contour in the first image and extracts a second feature from a second contour in the second image. The second calculating unit calculates a first difference between the first feature and the second feature. The determining unit determines a transparency that is higher as the first difference is larger. The generating unit generates a composite image combining the first image and the second image with the determined transparency.

Image processing device, method, and computer program product

Likelihood calculation means extracts audio features expressing features of a voice signal and a non-voice signal from an acquired audio signal, and calculates likelihood expressing probability that the voice signal is included in the audio signal using the audio features. Spectral feature extraction means performs a frequency analysis to the audio signal to extract a spectral feature. Using the spectral feature, first basis matrix producing means produces a first basis matrix expressing the feature of the non-voice signal. Second basis matrix producing means specifies a component having a high association with the voice signal in the first basis matrix using the likelihood, and excludes the component to produce a second basis matrix. Spectral feature estimation means estimates a spectral feature of the voice signal or a spectral feature of the non-voice signal by performing nonnegative matrix factorization to the spectral feature using the second basis matrix.

Audio signal processing apparatus and audio signal processing method

According to one embodiment, a video processing apparatus includes an acquisition unit, a first extraction unit, a generation unit, a second extraction unit, a computation unit and a selection unit. The acquisition unit is configured to acquire video streams. A first extraction unit is configured to analyze at least one of the moving pictures and the sounds for each video stream and to extract feature values. A generation unit is configured to generate segments by dividing each video stream, and to generate associated segment groups. A second extraction unit is configured to extract the associated segment groups that number of associated segments is greater than or equal to threshold as common video segment groups. A computation unit is configured to compute summarization score. A selection unit is configured to select segments used for a summarized video as summarization segments from the common video segment groups based on the summarization score.

Video processing apparatus, method and system

In an example signal clustering apparatus, a feature of a signal is divided into segments. A first feature vector of each segment is calculated, the first feature vector having has a plurality of elements corresponding to each reference model. A value of an element attenuates when a feature of the segment shifts from a center of a distribution of the reference model corresponding to the element. A similarity between two reference models is calculated. A second feature vector of each segment is calculated, the second feature vector having a plurality of elements corresponding to each reference model. A value of an element is a weighted sum and segments of second feature vectors of which the plurality of elements are similar values are clustered to one class.

Signal clustering apparatus

A video editing apparatusincludes a registering unitconfigured to register a key candidate having a feature vector of a sound signal which is determined to be registered on the basis of a co-occurrence score to a managing unitas a search key, and a cutting out unitconfigured to obtain an integration score in each of the blocks from the degree of similarity of the registered search key in each of the blocks and cut out a group of blocks exceeding an integration threshold value from among the integration scores as one video scene.

Video editing apparatus

An acquisition unit acquires feature vectors (the number is N). A first selection unit selects first neighbor features (k (1&#x2266;k&#x2266;N)) of each feature vector in order of higher similarity from the feature vectors. A second selection unit generates a plurality of groups each including similar feature vectors from the feature vectors, and selects second neighbor features (u (1&#x2266;k+u&#x2266;N&#x2212;2)) of each feature vector in order of higher similarity. Each of the second neighbor features is differently included in a group. A determination unit calculates a density of each feature vector by using a threshold, the first neighbor features and the second neighbor features, and determines feature vectors to be classified into the same class as each feature vector by using the density and a threshold. A classification unit classifies the feature vectors into a plurality of classes by using the selection result. A control unit controls each threshold.

Signal classification apparatus

A signal processing unit includes a feature quantity extracting unit, a segmentalizing unit, a clustering unit, an existence probability function deriving unit, an existence probability function similarity calculating unit, a cluster integrating unit and a cluster information output unit. The signal processing unit classifies the signal feature quantity which characterizes the content signal segmentalized into segments according to the similarity with respect to each other, obtains functions which indicate the existence probabilities for clusters of classified segments, and integrates the clusters whose obtained functions are at the high level of similarity.

Signal processing apparatus and method thereof

Acoustic models to provide features to a speech signal are created based on speech features included in regions where similarities of acoustic models created based on speech features in a certain time length are equal to or greater than a predetermined value. Feature vectors acquired by using the acoustic models of the regions and the speech features to provide features to speech signals of second segments are grouped by speaker.

Growing community of inventors

Kanagawa, Japan

Makoto Hirohata