Abstract: Speech recognition performance is improved without changing a speech recognition engine. A speech data generation section generates, from speech data for which speech recognition is to be performed, a plurality of pieces of speech data whose starting positions of the non-speech regions differ. A speech recognition engine performs speech recognition by using each of the pieces of speech data. A totaling/comparison section provides the most numerous recognized result from among a plurality of obtained recognized results.

Abstract: Alarm systems comprises an eye gaze direction detecting part, an obstacle detecting device and an alarm controlling part. The eye gaze direction detecting part determines a vehicle driver's field of view by analyzing facial images of a driver of the vehicle pictured by using a camera equipped in the vehicle. The obstacle detecting device detects the presence of an obstacle in the direction unobserved by the driver using a radar equipped in the vehicle, the direction of which radar is set up in the direction not attended by the driver on the basis of data detected by the eye gaze monitor. The alarm controlling part determines whether to make an alarm in case an obstacle is detected by the obstacle detecting device. The systems can detect the negligence of a vehicle driver in observing the front view targets and release an alarm to prevent the driver from any possible danger.

Abstract: Alarm systems comprises an eye gaze direction detecting part, an obstacle detecting device and an alarm controlling part. The eye gaze direction detecting part determines a vehicle driver's field of view by analyzing facial images of a driver of the vehicle pictured by using a camera equipped in the vehicle. The obstacle detecting device detects the presence of an obstacle in the direction unobserved by the driver using a radar equipped in the vehicle, the direction of which radar is set up in the direction not attended by the driver on the basis of data detected by the eye gaze monitor. The alarm controlling part determines whether to make an alarm in case an obstacle is detected by the obstacle detecting device. The systems can detect the negligence of a vehicle driver in observing the front view targets and release an alarm to prevent the driver from any possible danger.

Abstract: An input sound processor compares power at each frequency component of an input sound with a reference value, and sets multiplication points indicating frequency components at which the total power of the input sound is to be determined. A product-sum operation is performed at the multiplication points on the power at each frequency component and the square amplitude of each filter coefficient indicating the transfer characteristic from a loudspeaker to a microphone to estimate the total power of the input sound at the position of the microphone.

Abstract: On the basis of status information on a vehicle collected by a status information input interface from a navigation device, an ECU, and sensors, an S/N ratio estimating unit estimates, as an S/N ratio, the level of the ratio between the power of a component corresponding to audio-device output sound y(j) and that corresponding to noise sound n(j) contained in a microphone output signal. A transfer-function variation estimating unit estimates the level of a variation in a transfer function of an audio-device output audio signal transfer system. An adaptive characteristics controller controls a characteristic of a coefficient updating operation of a tap coefficient of an FIR filter performed by a coefficient updating unit of an adaptive filter, i.e., an adaptation (learning) characteristic of the adaptive filter, in response to the S/N ratio level and the level of the variation in the transfer function.

Abstract: The microphone system of the invention executes an adaptive filter processing by using output signals from two microphones to output a speaker's voice signal with an improved SN ratio, in which the two microphones are laid out close to each other, and the angles formed by the orientations of the microphones with respect to the speaker's vocalizing direction are made different for each of the microphones. For example, the microphones are mounted on the sun visor of a vehicle, or on the ceiling above the front passenger seat or the driver's seat of the vehicle, with the orientations of the microphones differentiated. Further, the SN ratio of the output signal from one microphone is raised, and the SN ratio of the output signal from the other microphone is lowered. For example, one microphone is positioned right above a speaker's face, and the other microphone is spaced apart on the occipital side by about 1 to 5 cm from the position of the first microphone.

Abstract: In a conventional device for extracting voice features accurately without being influenced by noises, such as a voice recognition device, usually an input voice signal is processed first by a noise reduction system having the tap length N, and the result is FFT-processed by L-points, and then the power spectrum vector is calculated; accordingly, a one time operation requires N multiplications and (N?1) summations. The voice feature extraction device according to the invention receives a voice signal including noises from a microphone, which is processed by a window function operation unit, and thereafter FFT-processed by an FFT operation unit by L-points. A power calculation unit calculates a power spectrum vector of the input voice signal. However, a noise reduction system determines in advance a filter coefficient of this system and processes the coefficient to calculate a noise reduction coefficient, and the power spectrum vector is processed by this noise reduction system.

Abstract: An input sound processor compares power at each frequency component of an input sound with a reference value, and sets multiplication points indicating frequency components at which the total power of the input sound is to be determined. A product-sum operation is performed at the multiplication points on the power at each frequency component and the square amplitude of each filter coefficient indicating the transfer characteristic from a loudspeaker to a microphone to estimate the total power of the input sound at the position of the microphone.

Abstract: The present invention provides a voice input apparatus which can extract an input voice without interrupting a generated background sound. When a talk switch 50 is pushed down, a LMS algorithm processing part 26 stops an update operation of a filter coefficient of an adaptive filter 24 and stores filter coefficient W1 at this moment in a portion for storing filter coefficients 30. A portion for calculating filter coefficients 44 calculates a filter coefficient W2 of a filter 42 to simulate a sound-transmittal line of an audio sound which is produced from a speaker 102 and is input into microphones 10, 12 by means of these stored filter coefficient W1 and various transmittal characteristics CS1, CS2 and the like. By extracting an output signal Y4 of the filter 42 from an output signal Y3 of a portion for eliminating surrounding noise 20 by means of a computing part 46, audio sound components included with an operating voice collected by the microphones 10, 12 are removed.

Abstract: Speech recognition performance is improved without changing a speech recognition engine. A speech data generation section generates, from speech data for which speech recognition is to be performed, a plurality of pieces of speech data whose starting positions of the non-speech regions differ. A speech recognition engine performs speech recognition by using each of the pieces of speech data. A totaling/comparison section provides the most numerous recognized result from among a plurality of obtained recognized results.

Abstract: In a conventional device for extracting voice features accurately without being influenced by noises, such as a voice recognition device, usually an input voice signal is processed first by a noise reduction system having the tap length N, and the result is FFT-processed by L-points, and then the power spectrum vector is calculated; accordingly, a one time operation requires N multiplications and (N−1) summations. The voice feature extraction device according to the invention receives a voice signal including noises from a microphone, which is processed by a window function operation unit, and thereafter FFT-processed by an FFT operation unit by L-points. A power calculation unit calculates a power spectrum vector of the input voice signal. However, a noise reduction system determines in advance a filter coefficient of this system and processes the coefficient to calculate a noise reduction coefficient, and the power spectrum vector is processed by this noise reduction system.