Abstract:
A referring expression processor which uses a probabilistic model and in which referring expressions including descriptive, anaphoric and deictic expressions are understood and generated in the course of dialogue is provided. The referring expression processor according to the present invention includes: a referring expression processing section which performs at least one of understanding and generation of referring expressions using a probabilistic model constructed with a referring expression Bayesian network, each referring expression Bayesian network representing relationships between a reference domain (D) which is a set of possible referents, a referent (X) in the reference domain, a concept (C) concerning the referent and a word (W) which represents the concept; and a memory which stores data necessary for constructing the referring expression Bayesian network.
Abstract:
A language understanding device includes: a language understanding model storing unit configured to store word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, and concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates including the predefined outputs, to accumulate word weights so as to obtain a cumulative word weight, and to sequentially perform state transition operations; a concept weighting processing unit configured to accumulate concept weights so as to obtain a cumulative concept weight; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates by referring to the cumulative word weight and the cumulative concept weight.
Abstract:
A speech recognition apparatus includes a speech input unit that receives input speech, a phoneme recognition unit that recognizes phonemes of the input speech and generates a first phoneme sequence representing corrected speech, a matching unit that matches the first phoneme sequence with a second phoneme sequence representing original speech, and a phoneme correcting unit that corrects phonemes of the second phoneme sequence based on the matching result.
Abstract:
A lexical acquisition apparatus includes: a phoneme recognition section 2 for preparing a phoneme sequence candidate from an inputted speech; a word matching section 3 for preparing a plurality of word sequences based on the phoneme sequence candidate; a discrimination section 4 for selecting, from among a plurality of word sequences, a word sequence having a high likelihood in a recognition result; an acquisition section 5 for acquiring a new word based on the word sequence selected by the discrimination section 4; a teaching word list 4A used to teach a name; and a probability model 4B of the teaching word and an unknown word, wherein the discrimination section 4 calculates, for each word sequence, a first evaluation value showing how much words in the word sequence correspond to teaching words in the list 4A and a second evaluation value showing a probability at which the words in the word sequence are adjacent to one another and selects a word sequence for which a sum of the first evaluation value and the second evaluation value is maximum, and wherein the acquisition section 5 acquires, as a new word, a word in the word sequence selected by the discrimination section that is not involved in the calculation of the first evaluation value.
Abstract:
The invention provides a dialogue-based learning apparatus through dialogue with users comprising: a speech input unit (10) for inputting speeches; a speech recognition unit (20) for recognizing the input speech; and a behavior and dialogue controller (30) for controlling behaviors and dialogues according to speech recognition results, wherein the behavior and dialogue controller (30) has a topic recognition expert (34) to memorise contents of utterances and to retrieve the topic that best matches the speech recognition results, and a mode switching expert (35) to control mode switching in accordance with a user utterance, wherein the mode switching expert switches modes in accordance with a user utterance, wherein the topic recognition expert registers a plurality words in the utterance as topics in first mode, performs searches from among the registered topics, and selects the maximum likelihood topic in second mode.
Abstract:
A language understanding device includes: a language understanding model storing unit configured to store word transition data including pre-transition states, input words, predefined outputs corresponding to the input words, word weight information, and post-transition states, and concept weighting data including concepts obtained from language understanding results for at least one word, and concept weight information corresponding to the concepts; a finite state transducer processing unit configured to output understanding result candidates including the predefined outputs, to accumulate word weights so as to obtain a cumulative word weight, and to sequentially perform state transition operations; a concept weighting processing unit configured to accumulate concept weights so as to obtain a cumulative concept weight; and an understanding result determination unit configured to determine an understanding result from the understanding result candidates by referring to the cumulative word weight and the cumulative concept weight.
Abstract:
A speech recognition apparatus includes a speech input unit that receives input speech, a phoneme recognition unit that recognizes phonemes of the input speech and generates a first phoneme sequence representing corrected speech, a matching unit that matches the first phoneme sequence with a second phoneme sequence representing original speech, and a phoneme correcting unit that corrects phonemes of the second phoneme sequence based on the matching result.
Abstract:
A referring expression processor which uses a probabilistic model and in which referring expressions including descriptive, anaphoric and deictic expressions are understood and generated in the course of dialogue is provided. The referring expression processor according to the present invention includes: a referring expression processing section which performs at least one of understanding and generation of referring expressions using a probabilistic model constructed with a referring expression Bayesian network, each referring expression Bayesian network representing relationships between a reference domain (D) which is a set of possible referents, a referent (X) in the reference domain, a concept (C) concerning the referent and a word (W) which represents the concept; and a memory which stores data necessary for constructing the referring expression Bayesian network.
Abstract:
A lexical acquisition apparatus includes: a phoneme recognition section 2 for preparing a phoneme sequence candidate from an inputted speech; a word matching section 3 for preparing a plurality of word sequences based on the phoneme sequence candidate; a discrimination section 4 for selecting, from among a plurality of word sequences, a word sequence having a high likelihood in a recognition result; an acquisition section 5 for acquiring a new word based on the word sequence selected by the discrimination section 4; a teaching word list 4A used to teach a name; and a probability model 4B of the teaching word and an unknown word, wherein the discrimination section 4 calculates, for each word sequence, a first evaluation value showing how much words in the word sequence correspond to teaching words in the list 4A and a second evaluation value showing a probability at which the words in the word sequence are adjacent to one another and selects a word sequence for which a sum of the first evaluation value and the second evaluation value is maximum, and wherein the acquisition section 5 acquires, as a new word, a word in the word sequence selected by the discrimination section that is not involved in the calculation of the first evaluation value.
Abstract:
An image capturing device is equipped with an external parameter estimating unit for estimating external parameters using a distance image obtained by a TOF camera and a luminance image obtained by a CCD camera, a corresponding pixel determining unit for determining a correspondence relationship between pixel positions in the distance image and pixel positions in the luminance image, using previously stored internal parameters of the TOF camera and the CCD camera or the CCD camera, and the external parameters, and an occlusion searching unit for searching for an occlusion region in the distance image, using the correspondence relationship between pixel positions in the distance image and pixel positions in the luminance image.