Sony Corporation

So-net Entertainment Corporation

Hitoshi Honda

Hiroaki Ogawa

Naoto Iwahashi

Masanori Omote

Yoshinori Maeda

Hongchang Bao

Kazuo Ishii

Keiichi Yamada

Katsuki Minamino

Hongchang Pao

Junichi Yamashita

Junichi Rekimoto

Hiroaki Kitano

Yasuharu Asano

Kazuo Watanabe

Yasuhiko Kato

Satoshi Fujimura

Hiroshi Kakuda

Makoto Akabane

Miyuki Tanaka

Masato Shimakawa

Atsuo Hiroe

Masao Watari

Hideshi Tamaru

Motoki Nakade

Helmut Lucke

Yoshinori Kurata

Yaeko Fujita

Satoshi Asakawa

Daisuke Ishizuka

Bao Hongchang

Kazunori Sasano

The present invention relates to a searching device, searching method, and program whereby searching for a word string corresponding to input voice can be performed in a robust manner. A voice recognition unitsubjects an input voice to voice recognition. A matching unitperforms matching, for each of multiple word strings for search results which are word strings that are to be search results for word strings corresponding to the input voice, of a pronunciation symbol string for search results, which is an array of pronunciation symbols expressing pronunciation of the word string search result, and a recognition result pronunciation symbol string which is an array of pronunciation symbols expressing pronunciation of the voice recognition results of the input voice. An output unitoutputs a search result word string which is the result of searching the word strings corresponding to the input voice from the multiple word strings for search results, based on the matching results of the pronunciation symbol string for search results and the recognition result pronunciation symbol string. The present invention can be applied in the case of performing voice searching, for example.

Speech-based pronunciation symbol searching device, method and program using correction distance

A search apparatus includes: a speech recognition unit that recognizes an input voice; a matching unit that matches a plurality of strings of search result target words; a generation unit that generates a string of search result words; a selecting unit that selects emphasis target words that are the targets to be emphasized in the words of the string of search result words, on the basis of the matching result with the string of search result target words, and a pronunciation symbol-to-word table in which the pronunciation symbols and the words are made to correspond to each other; and a conversion unit that converts the string of search result words into the string of emphasis words in which the emphasis target words are emphasized in the words of the string of search result words.

Search apparatus, search method, and program

A voice chat system includes a plurality of information processing apparatuses that performs a voice chat while performing speech recognition and a search server connected to the plural information processing apparatuses via a communication network. The search server discloses a search keyword list containing the search keywords searched by the search server to at least one of the plural information processing apparatuses. The at least one information processing apparatus includes a recognition word dictionary generating unit that acquires the search keyword list from the search server to generate a recognition word dictionary containing words for use in the speech recognition, and a speech recognition unit that performs speech recognition on voice data obtained from a dialog of the conversation during the voice chat by referencing a recognition database containing the recognition word dictionary.

Voice chat system, information processing apparatus, speech recognition method, keyword data electrode detection method, and program for speech recognition

There is provided a voice processing device. The device includes: score calculation unit configured to calculate a score indicating compatibility of a voice signal input on the basis of an utterance of a user with each of plural pieces of intention information indicating each of a plurality of intentions; intention selection unit configured to select the intention information indicating the intention of the utterance of the user among the plural pieces of intention information on the basis of the score calculated by the score calculation unit; and intention reliability calculation unit configured to calculate the reliability with respect to the intention information selected by the intention selection unit on the basis of the score calculated by the score calculation unit.

Voice processing device and method, and program

A search apparatus includes a sound recognition unit which recognizes input sound, a user information estimation unit which estimates at least one of a physical condition and emotional demeanor of a speaker of the input sound based on the input sound and outputs user information representing the estimation result, a matching unit which performs matching between a search result target pronunciation symbol string and a recognition result pronunciation symbol string for each of plural search result target word strings, and a generation unit which generates a search result word string as a search result for a word string corresponding to the input sound from the plural search result target word strings based on the matching result. At least one of the matching unit and the generation unit changes processing in accordance with the user information.

A signal processing device for processing an input signal includes gain calculating means and feature quantity calculating means. The gain calculating means is configured to obtain information indicating magnitude of noise to be added to the input signal on a basis of periodicity information indicating periodicity of the input signal and power of the input signal. The feature quantity calculating means is configured to obtain periodicity information of a noise-added signal obtained by adding noise having magnitude corresponding to the gain information to the input signal as a feature quantity of the input signal.

Signal processing device, signal processing method, and program

It is intended to increase the recognition rate in speech recognition and image recognition. An observation vector as input data, which represents a certain point in the observation vector space, is mapped to a distribution having a spread in the feature vector space, and a feature distribution parameter representing the distribution is determined. Pattern recognition of the input data is performed based on the feature distribution parameter.

Feature extraction apparatus and method and pattern recognition apparatus and method

A speech processing system including a speech recognition unit to receive input speech, and a natural language processing unit. The speech recognition unit performs speech recognition on input speech using acoustic models to produce a speech recognition result. The natural-language processing unit performs natural language processing on the speech recognition result, and includes: a machine translation unit; a dialog management unit; and a feedback unit. The feedback unit configured to feed back information obtained as a result of the natural language processing performed in the machine translation unit and the dialog management unit. The speech recognition unit processes feedback information including adaptation zones to adapt the acoustic models so that it can produce the speech recognition result with higher precision than when adaptation zones are not used.

Speech recognition with feedback from natural language processing for adaptation of acoustic model

A feature extraction and pattern recognition system in which an observation vector forming input data, which represents a certain point in the observation vector space, is mapped to a distribution having a spread in the feature vector space, and a feature distribution parameter representing the distribution is determined. Pattern recognition of the input data is performed based on the feature distribution parameter.

A speech recognition unit performs speech recognition on input speech based on models, such as HMMs, and supplies a speech recognition result to a dialog management unit. The dialog management unit forms a reply to the speech recognition result. In this case, the dialog management unit detects zones in which the speech recognition result is correct based on the speech recognition result and the associated reply, and feeds them back to the speech recognition unit. Then, the speech recognition unit performs on-line adaptation of the models based on the speech of the correct zones fed back from the dialog management unit and the associated speech recognition result.

Speech recognition with feedback from natural language processing for adaptation of acoustic models

Information processing device, information processing method and storage medium

An information processing system stores information of various types, which is obtained in the real world, in connection with keys indicative of the attribute and feature of the information so that the real-world information is stored quickly and surely in the virtual world which is formed of the linkage of information and stored information of various types is retrieved easily.

Information processing apparatus and information processing method

A mapping determination method for obtaining mapping F from an N-dimensional metric vector space .OMEGA..sub.N to an M-dimensional metric vector space .OMEGA..sub.M has the following steps to get the optimal mapping quickly and positively. In the first step, complete, periodic, L.sub.m basic functions g.sub.m (X) according to the distribution of samples classified into Q categories on the N-dimensional metric vector space .OMEGA..sub.N are set. In the second step, a function f.sub.m (X) indicating the m-th component of the mapping F is expressed with the linear sum of the functions g.sub.m (X) and L.sub.m coefficients c.sub.m. The third step provides Q teacher vectors T.sub.q =(t.sub.q.1, t.sub.q.2, t.sub.q.3, . . . , t.sub.q.M) (where q=1, 2, . . . , Q) for the categories on the M-dimensional metric vector space .OMEGA..sub.M, calculates the specified estimation function J, and obtains the coefficients c.sub.m which minimize the estimation function J. In the fourth step, the coefficients c.sub.m obtained in the third step are stored in memory.

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Tokyo, Japan

Hitoshi Honda