Abstract: A moving object 1 equipped with ultra-directional speaker is provided with an emitter 44 for measuring a distance to a target 11 to which it is to provide a voice by using an ultrasonic transmit sensor 45 and an ultrasonic receive sensor 46 thereof, and for emitting an output signal having a predetermined sound level which is adjusted by an amplifier 34 with sound level adjusting function. The moving object 1 can thus transmit a voice having an optimal volume only to the specific target through parametric action.

Abstract: There is provided a sound source characteristic determining device (10) capable of being applied in an environmental where the type of a sound source is unknown. The device includes a plurality of beamformers (21-1 to 21-M) used when a sound source signal generated from a sound source at an arbitrary position in a space is inputted to a plurality of microphones (14-1 to 14-N), for weighting the acoustic signal detected by each of the microphones by using a function for correcting the difference of the sound source signals generated between the microphones and outputting a totaled signal. Each of the beamformers (21-1 to 21-M) contains a function having a unit directivity characteristic corresponding to one arbitrary direction in the space and is arranged for each of the directions corresponding to an arbitrary position in the space and the unit directivity characteristic.

Abstract: A voice recognition system (10) for improving the toughness of voice recognition for a voice input for which a deteriorated feature amount cannot be completely identified. The system comprises at least two sound detecting means (16a, 16b) for detecting a sound signal, a sound source localizing unit (21) for determining the direction of a sound source based on the sound signal, a sound source separating unit (23) for separating a sound by the sound source from the sound signal based on the sound source direction, a mask producing unit (25) for producing a mask value according to the reliability of the separation results, a feature extracting unit (27) for extracting the feature amount of the sound signal, and a voice recognizing unit (29) for applying the mask to the feature amount to recognize a voice from the sound signal.

Abstract: A robot that recognizes speech of a person while performing predetermined motions or gestures, the robot includes: a drive unit executing the motions or gestures; a determination unit determining one of the motions or gestures being executed; a speech recognition unit having at least two recognition algorithms including a multi-condition training algorithm; and a switch unit selecting one of the recognition algorithms depending on one of the motions or gestures determined.

Abstract: An object detection apparatus and method capable of detecting objects based on visual images captured by a self-moving unit. A sequential images output section makes a train of a first input image and a second input image sequential to the first input image and outputs said train. A local area image processor calculates local flows based on said first input image and said second input image. An inertia information acquiring section measures self-motion of the unit to calculate inertia information thereof. A global area image processor uses said inertia information to estimate global flow, which is a motion field of the entire view associated to the self-motion, using said global flow and said first input image and creates a predictive image of said second input image. The global area image processor then calculates differential image data, which is a difference between said predictive image and said second input image.

Abstract: An ultra-directional speaker having a modulator 33 for modulating an ultrasonic carrier signal with an input electric signal from an audible sound signal source, and an emitter 44 for emitting an output of the modulator 33 is mounted in a moving object 1 having a target tracking system for sensing a target in a surrounding space in real time using the above-mentioned emitter 44. The moving object equipped with ultra-directional speaker can therefore transmit a voice only to a specific target through parametric action caused by the nonlinearity of finite amplitude of ultrasonic wave.

Abstract: A moving object 1 equipped with ultra-directional speaker is provided with an emitter 44 for measuring a distance to a target 11 to which it is to provide a voice by using an ultrasonic transmit sensor 45 and an ultrasonic receive sensor 46 thereof, and for emitting an output signal having a predetermined sound level which is adjusted by an amplifier 34 with sound level adjusting function. The moving object 1 can thus transmit a voice having an optimal volume only to the specific target through parametric action.

Abstract: An image recognizing apparatus and method is provided for recognizing behavior of a mobile unit accurately with an image of external environment acquired during the mobile unit is moving. Behavior command output block 12 outputs behavior commands to cause the mobile unit 32 move. Local feature extraction block 16 extracts features of local areas of the image from the image of external environment acquired on the mobile unit 32 when the behavior command is output. Global feature extraction block 18 extracts feature of global area of the image using the features of local areas. Learning block 20 calculates probability models for recognizing behavior given to the mobile unit 32 based on the feature of global area of the image. After learning is finished, behavior of the mobile unit 32 may be recognized rapidly and accurately by applying the probability models to an image of external environment acquired in mobile unit 32 afresh.

Abstract: A production device and method which produce a multiple-system film having metal components such as TiAlN greatly different in melting point by a melting-evaporation type ion plating method that provides a high material utilization efficiency and a good film quality. Power needed to evaporate a material (4) is first supplied, and then power gradually increased over the initail power is repeatedly supplied until a needed maximum power is reached. Concurrently, a plasma control is performed for converging plasma (7) onto an initial area needed to evaporate the material, and then a plasma control is performed for continuously and sequentially moving/expanding plasma from the initial plasma area up to a maximum plasma area to thereby gradually melt the non-melted portion of the material.

Abstract: It is objective of the invention to provide a highly reliable control apparatus and method which reduces the amount of calculation required for both learning of an input/output relationship and actual control as well as prevent inappropriate outputs from being generated for inputs which have been never learned. According to one aspect of the invention, pairs of an input pattern vector for learning and a target output are distributed to a class based on the target output. Then, a correspondence between each element of the input pattern vector for learning and the target output is learned only in that class, and a distribution function is calculated for distributing a new input pattern vector for learning to that class. After the completion of this learning, the distribution function is used to determine which class a new input pattern vector detected by a sensor belongs to. Finally, an output is calculated according to the learning result of that class.

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: An agent learning apparatus comprises a sensor (301) for acquiring a sense input, an action controller (307) for creating an action output in response to the sense input and giving the action output to a controlled object, an action state evaluator (303) for evaluating the behavior of the controlled object, a selective attention mechanism (304) for storing the action output and the sense input corresponding to the action output in one of the columns according to the evaluation, calculating a probability model from the action outputs stored in the columns, and outputting, as a learning result, the action output related to a newly given sense input in the column where the highest confidence obtained by applying the newly given sense input to the probability model is stored. By thus learning, the selective attention mechanism (304) obtains a probability relationship between the sense input and the column. An action output is calculated on the basis of the column evaluated as a stable column.

Abstract: A sound separation apparatus for separating a target signal from a mixed input signal, wherein the mixed input signal includes the target signal and one or more sound signals emitted from different sound sources. The sound separation apparatus according comprises a frequency analyzer for performing a frequency analysis on the mixed input signal and calculating spectrum and frequency component candidate points at each time. The apparatus further comprises feature extraction means for extracting feature parameters which are estimated to correspond with the target signal, comprising a local layer for analyzing local feature parameters using the spectrum and the frequency component candidate points and one or more global layers for analyzing global feature parameters using the feature parameters extracted by the local layer. The apparatus further comprises a signal regenerator for regenerating a waveform of the target signal using the feature parameters extracted by the feature extraction means.

Abstract: An object detection apparatus is provided for detecting both stationary objects and moving objects accurately from an image captured from a moving mobile unit. The object detection apparatus of the present invention applies Gabor filter to two or more input images captured by an imaging device such as CCD camera mounted on a mobile unit, and calculates optical flow of local areas in the input images. Then the object detection apparatus closely removes optical flow produced by motion of the mobile unit by estimating optical flow produced from background of the input images. In other words, the object detection apparatus clarifies the area where object is not present (“ground”) in the input images. By removing such “ground” part, the area where objects seems to be present (“feature”) is extracted from the input images. Finally, the object detection apparatus determines whether objects are present or not using flow information of the extracted “feature” part.

Abstract: The invention relates to a behavior control apparatus and method for autonomously controlling a mobile unit based on visual information in practical application without the needs of a greatdeal of preparation or computational cost and limiting the type of target object. According to one aspect of the invention, a method for controlling behavior of a mobile unit using behavior command is provided. First, sensory inputs are captured and then the motion of the mobile unit is estimated. The portion which includes a target object to be target for behavior of the mobile unit is segregated from the sensory inputs. The target objects extracted from the segregated portion and the location of the target object is acquired. Finally, the mobile unit is controlled based on the location of target object.

Abstract: An information transmission device which analyzes a diction of a speaker and provides an utterance in accordance with the diction of the speaker, and which has a microphone detecting a sound signal of the speaker, a feature extraction unit extracting at least one feature value of the diction of the speaker based on the sound signal detected by the microphone, a voice synthesis unit synthesizing a voice signal to be uttered so that the voice signal has the same feature value as the diction of the speaker, based on the feature value extracted by the feature extraction unit, and a voice output unit performing an utterance based on the voice signal synthesized by the voice synthesis unit.

Abstract: A motion information recognition system takes time-series images of an object in motion and generates image vectors that are analyzed to produce a plurality of eigenvectors that are then stored. Inner product operations are performed between image vectors of a recognized object and a plurality of the stored eigenvectors for obtaining the motion information of the recognized object based on the result of said inner product operations to provide high-speed and easy motion information recognition at reduced computing cost.

Abstract: An object detection apparatus and method capable of detecting objects based on visual images captured by a self-moving unit. A sequential images output section makes a train of a first input image and a second input image sequential to the first input image and outputs said train. A local area image processor calculates local flows based on said first input image and said second input image. An inertia information acquiring section measures self-motion of the unit to calculate inertia information thereof. A global area image processor uses said inertia information to estimate global flow, which is a motion field of the entire view associated to the self-motion, using said global flow and said first input image and creates a predictive image of said second input image. The global area image processor then calculates differential image data, which is a difference between said predictive image and said second input image.