Abstract: A robot includes: a sound collecting unit collecting and converting a musical sound into a musical acoustic signal; a voice signal generating unit generating a self-vocalized voice signal; a sound outputting unit converting the self-vocalized voice signal into a sound and outputting the sound; a self-vocalized voice regulating unit receiving the musical acoustic signal and the self-vocalized voice signal; a filtering unit performing a filtering process; a beat interval reliability calculating unit performing a time-frequency pattern matching process and calculating a beat interval reliability; a beat interval estimating unit estimating a beat interval; a beat time reliability calculating unit calculating a beat time reliability; a beat time estimating unit estimating a beat time on the basis of the calculated beat time reliability; a beat time predicting unit predicting a beat time before the current time; and a synchronization unit synchronizing the self-vocalized voice signal.

Abstract: A system capable of reducing the influence of sound reverberation or reflection to improve sound-source separation accuracy. An original signal X(?,f) is separated from an observed signal Y(?,f) according to a first model and a second model to extract an unknown signal E(?,f). According to the first model, the original signal X(?,f) of the current frame f is represented as a combined signal of known signals S(?,f?m+1) (m=1 to M) that span a certain number M of current and previous frames. This enables extraction of the unknown signal E(?,f) without changing the window length while reducing the influence of reverberation or reflection of the known signal S(?,f) on the observed signal Y(?,f).

Abstract: A trajectory planning system obtains a trajectory for controlling a state of an object toward a goal state. The system includes a search tree generating section which registers a state of the object as a root of a search tree in a state space, registers a next state of the object after a lapse of a predetermined time interval obtained through dynamical relationships during the time interval as a branch of the search tree in the state space.

Abstract: A thereminist robot has a characteristic model of theremin and is capable of performing in response to an environment of theremin performance by calibrating the characteristic model before the performance. A robot 10 has a first arm 12, a second arm 11, and a pitch model for indicating an arm position corresponding to a pitch of the theremin The robot 10 plays the theremin by moving the first arm 12 to the arm position corresponding to a musical note based on the target note and the pitch model.

Abstract: A learning control system according to the present invention is one which performs learning of action values of actions in an apparatus which identifies its state as one of predetermined states, and selects an action based on the obtained action values and the identified state. The learning control system includes n action value learning devices including the first to the n th learning devices which perform learning of n action values from Q1 to Qn, assuming that n is a positive integer and an action value determining device which determines the total action value of an action Q of each state based on outputs of the n action value learning devices.

Abstract: An acoustic data processor according to the present invention is used for processing acoustic data including signal sounds to reduce noises generated by a mechanical apparatus. The acoustic data processor includes a motion status obtaining section for obtaining motion status of the mechanical apparatus, an acoustic data obtaining section for obtaining acoustic data corresponding to the obtained motion status, and a database for storing various motion statuses of the mechanical apparatus in a unit time and corresponding acoustic data as templates. The acoustic data processor further includes a database searching section for searching the database to retrieve the template having the motion status closest to the obtained motion status; and a template subtraction section for subtracting the acoustic data of the template having the motion status closest to the obtained motion status from the obtained acoustic data to reduce noises generated by the mechanical apparatus.

Abstract: A face recognition system includes a component learning/extraction module, component classifier training module, knowledge base for component classification (KBCC), component extraction module (CEM), object identification training module (OITM), knowledge base for face identification (KBFI), and object identification module (OIM). The CEM receives image data of faces at various viewpoints and extracts outputs of classification of the component data, using the results of classifier training of the component data, stored in the KBCC. The OITM receives the outputs of classification of the component data and determines indicator component for each person by Bayesian estimation so that posterior probability of a predetermined attention class is maximized under the outputs of classification of the component data at various viewpoints. The KBFI stores indicator components for the individuals.

Abstract: In a sound source localization system using a light emitting device for visualizing sound information, including: a light emitting device (40) including a microphone for receiving sound from a sound source (1, 2) and a light emitting means for emitting light based on the sound from the microphone; a generating section for generating light emitting information for the light emitting device (40); and a sound source localization section (60) for determining a position of the sound source based on the light emitting information from the generating section.

Abstract: A learning system according to the present invention includes an event list database for storing a plurality of event lists, each of the event lists being a set including a series of state-action pairs which reaches a state-action pair immediately before earning a reward, an event list managing section for classifying state-action pairs into the plurality of event lists for storing, and a learning control section for updating expectation of reward of a state-action pair which is an element of each of the event lists.

Abstract: Provided is a dereverberation system or the like which copes with an arbitrary condition flexibly and is capable of recognizing a sound or a sound source signal. According to the dereverberation system, an inverse filter (h) is set by using a pseudo-inverse matrix (R+) of a non-square matrix (R) as a correlation matrix of input signals (x). On the basis of the inverse filter (h) and an estimated correlation matrix (R?) generated according to a window function (w), an error cost (J(h) between a correlation value of the input signals (x) and output signals (y) and a desired correlation value (d) is calculated. On the basis of the error cost (J(h)), the inverse filter (h) is adaptively updated according to a gradient method.

Abstract: A neural network element, outputting an output signal in response to a plurality of input signals, comprises a history memory for accumulating and storing the plurality of input signals in a temporal order as history values. It also includes an output module for outputting the output signal when an internal state exceeds a predetermined threshold value, the internal state being based on a sum of the product of a plurality of input signals and corresponding coupling coefficients. The history values depend on change of the internal state. The neural network element is configured to subtract a predetermined value from the internal state immediately after the output module fires and performs learning for reinforcing or attenuating the coupling coefficient according to the history values after the output module fires.

Abstract: A result of a sound source direction measurement based on an output of an REMA (first microphone array) (11) and a result of a sound source position measurement based on an output of an IRMA (second microphone array) (12) are integrated through a particle filter or in space. Thus, the different microphones, i.e., the REMA (11) and the IRMA (12) can cancel mutual defects or ambiguities with each other. Therefore, from views of improvement in accuracy and robustness a performance of sound source localization can be improved.

Abstract: A robot includes: a sound collecting unit collecting and converting a musical sound into a musical acoustic signal; a voice signal generating unit generating a self-vocalized voice signal; a sound outputting unit converting the self-vocalized voice signal into a sound and outputting the sound; a self-vocalized voice regulating unit receiving the musical acoustic signal and the self-vocalized voice signal; a filtering unit performing a filtering process; a beat interval reliability calculating unit performing a time-frequency pattern matching process and calculating a beat interval reliability; a beat interval estimating unit estimating a beat interval; a beat time reliability calculating unit calculating a beat time reliability; a beat time estimating unit estimating a beat time on the basis of the calculated beat time reliability; a beat time predicting unit predicting a beat time before the current time; and a synchronization unit synchronizing the self-vocalized voice signal.

Abstract: A beat tracking apparatus includes: a filtering unit configured to perform a filtering process on an input acoustic signal and to accentuate an onset; a beat interval reliability calculating unit configured to perform a time-frequency pattern matching process employing a mutual correlation function on the acoustic signal of which the onset is accentuated and to calculate a beat interval reliability; and a beat interval estimating unit configured to estimate a beat interval on the basis of the calculated beat interval reliability.

Abstract: The game device of the present invention comprises a first image processing means for generating an image captured from the view of a virtual camera which moves together with a virtual player on landforms in a game world and displaying it as a main screen, a second image processing means for generating an image on which a destination for the virtual player can be designated and displaying it as a map image, a destination designation means for designating a destination for the virtual player, route determination means for detecting the position of a destination for the virtual player designated on the map screen, determining the shortest route connecting the detection position of the destination and the present position of the virtual player, and determining a movement route for the virtual player, and a movement control means for allowing the virtual player to move to the destination along the movement route.

Abstract: A device capable of improving the convergence rate and estimation accuracy in estimating a correlation value. According to a signal processing device, since a window length is adjusted in such a manner to reduce an estimated error of a correlation matrix, the convergence rate and estimation accuracy in estimating the correlation matrix and the correlation value as its off-diagonal element can be improved. Then, in such a high-probability condition that the correlation of plural output signals according to a state is estimated with a high degree of precision, signal processing is performed on the plural signals, so that the state can be estimated with a high degree of precision.

Abstract: A system capable of reducing the influence of sound reverberation or reflection to improve sound-source separation accuracy. An original signal X(?,f) is separated from an observed signal Y(?,f) according to a first model and a second model to extract an unknown signal E(?,f). According to the first model, the original signal X(?,f) of the current frame f is represented as a combined signal of known signals S(?,f?m+1) (m=1 to M) that span a certain number M of current and previous frames. This enables extraction of the unknown signal E(?,f) without changing the window length while reducing the influence of reverberation or reflection of the known signal S(?,f) on the observed signal Y(?,f).

Abstract: An automatic speech recognition system includes: a sound source localization module for localizing a sound direction of a speaker based on the acoustic signals detected by the plurality of microphones; a sound source separation module for separating a speech signal of the speaker from the acoustic signals according to the sound direction; an acoustic model memory which stores direction-dependent acoustic models that are adjusted to a plurality of directions at intervals; an acoustic model composition module which composes an acoustic model adjusted to the sound direction, which is localized by the sound source localization module, based on the direction-dependent acoustic models, the acoustic model composition module storing the acoustic model in the acoustic model memory; and a speech recognition module which recognizes the features extracted by a feature extractor as character information using the acoustic model composed by the acoustic model composition module.

Abstract: A first domain satisfying a first condition concerning a current utterance understanding result and a second domain satisfying a second condition concerning a selection history are specified. For each of the first and second domains, indices representing reliability in consideration of the utterance understanding history, selection history, and utterance generation history are evaluated. Based on the evaluation results, one of the first, second, and third domains is selected as a current domain according to a selection rule.

Abstract: A system capable of separating sound source signals with high precision while improving a convergence rate and convergence precision. A process of updating a current separation matrix Wk to a next separation matrix Wk+1 such that a next value J(Wk+1) of a cost function is closer to a minimum value J(W0) than a current value J(Wk) is iteratively performed. An update amount ?Wk of the separation matrix is increased as the current value J(Wk) of the cost function is increased and is decreased as a current gradient ?J(Wk)/?W of the cost function is rapid. On the basis of input signals x from a plurality of microphones Mi and an optimal separation matrix W0, it is possible to separate sound source signals y(=W0·x) with high precision while improving a convergence rate and convergence precision.