Abstract: A system for voice detection includes a feature value calculation unit that calculates a feature value from an input signal sliced on a per frame basis, a provisional voice/non-voice decision unit that provisionally decides a voiced interval and a non-voiced interval from the feature value calculated on a per frame basis, and a voice/non-voice decision unit that determines a voiced interval duration threshold value or a non-voiced interval duration threshold value, using a ratio of the feature value found on a per frame basis to a threshold value for the feature value and that re-decides the voiced interval and the non-voiced interval, using the voiced interval duration threshold value determined and the non-voiced interval duration threshold value determined.

Abstract: A voice recognition device that recognizes a voice of an input voice signal, comprises a voice model storage unit that stores in advance a predetermined voice model having a plurality of detail levels, the plurality of detail levels being information indicating a feature property of a voice for the voice model; a detail level selection unit that selects a detail level, closest to a feature property of an input voice signal, from the detail levels of the voice model stored in the voice model storage unit; and a parameter setting unit that sets parameters for recognizing the voice of an input voice according to the detail level selected by the detail level selection unit.

Abstract: To this end, a voice detection device includes a band-based power calculation unit that calculates a total of signal power values (sub-band power) of signals entered from the microphones from one preset frequency width (sub-band) to another. The voice detection device also includes a band-based noise estimation unit that estimates the sub-band based noise power, and a sub-band based SNR calculation unit. The sub-band based SNR calculation unit calculates a sub-band SNR from one sub-band to another to output the largest one of the sub-band SNRs as an SNR for a microphone of interest. The voice detection device further includes a voice/non-voice decision unit that determines the voice/non-voice using the SNR for the microphone of interest.

Abstract: Disclosed is a gain control system in which speech model constituted from a sound pressure and a feature is stored in a speech model storage unit for each of a plurality of phonemes or for each of clusters into which a speech is divided. When an input signal is given, a feature conversion unit calculates a feature and a sound pressure of the input signal. A sound pressure comparison unit determines a sound pressure ratio between the input signal and each of speech models. A distance calculation unit calculates a distance between the feature of the input signal and the feature of each of the speech models. A gain calculation unit calculates a gain value from the sound pressure ratio and information on the distance. A sound pressure compensation unit thereby compensates for the sound pressure of the input signal.

Abstract: A method for processing multichannel acoustic signals, whereby input signals of a plurality of channels including the voices of a plurality of speaking persons are processed. The method is characterized by comprising: calculating the first feature quantity of the input signals of the multichannels for each channel; calculating similarity of the first feature quantity of each channel between the channels; selecting channels having high similarity; separating signals using the input signals of the selected channels; inputting the input signals of the channels having low similarity and the signals after the signal separation; and detecting a voice section of each speaking person or each channel.

Abstract: A method for processing multichannel acoustic signals which is characterized by calculating the feature quantity of each channel from the input signals of a plurality of channels, calculating similarity between the channels in the feature quantity of each channel, selecting channels having high similarity, and separating signals using the input signals of the selected channels.

Abstract: A method for processing multichannel acoustic signals which processes input signals of a plurality of channels including the voices of a plurality of speaking persons. The method is characterized by detecting the voice section of each speaking person or each channel, detecting overlapped sections wherein the detected voice sections are common between channels, determining a channel to be subjected to crosstalk removal and the section thereof by use of at least voice sections not including the detected overlapped sections, and removing crosstalk in the sections of the channel to be subjected to the crosstalk removal.

Abstract: Judgment result deriving means 74 makes a judgment between active voice and non-active voice every unit time for a time series of voice data in which the number of active voice segments and the number of non-active voice segments are already known as a number of the labeled active voice segment and a number of the labeled non-active voice segment and shapes active voice segments and non-active voice segments as the result of the judgment by comparing the length of each segment during which the voice data is consecutively judged to correspond to active voice by the judgment or the length of each segment during which the voice data is consecutively judged to correspond to non-active voice by the judgment with a duration threshold. Segments number calculating means 75 calculates the number of active voice segments and the number of non-active voice segments.

Abstract: A frame extracting means 71 extracts frames from sample data as voice data in which whether each frame is an active voice frame or a non-active voice frame is already known. A feature quantity calculating means 72 calculates multiple feature quantities of each of the frames. A feature quantity integrating means 73 calculates an integrated feature quantity of the multiple feature quantities. A judgment means 74 judges whether each of the frames is an active voice frame or a non-active voice frame. An erroneous feature quantity calculation value calculating means 75 obtains a first erroneous feature quantity calculation value and a second erroneous feature quantity calculation value by executing prescribed calculations. A weight updating means 76 updates weights used for weighting so that the rate between the first erroneous feature quantity calculation value and the second erroneous feature quantity calculation value approaches a prescribed value.

Abstract: A signal correction apparatus receives an input audio signal (serving as a first sound reception means). The signal correction apparatus computes, at every frequency, first power that indicates magnitude of sound represented by the input audio signal (serving as a first power computation means). The signal correction apparatus estimates a correction function that is a continuous function defining a relation between each frequency and a correction coefficient used to approximate the first power computed at that frequency to the reference power predetermined for that frequency (serving as a correction function estimation means). The signal correction apparatus multiplies the computed first power by the correction coefficient acquired in accordance with the relation defined by the estimated correction function so as to correct the first power at every frequency (serving as a power correcting means).

Abstract: A speech sound detection apparatus receives an input audio signal (as a sound reception unit), and computes input power that indicates a magnitude of the sound represented by the audio signal (as an input power computation unit). The apparatus estimates a correction function that is a continuous function defining a relation between a certain frequency and a correction coefficient used to approximate the input power computed at that frequency to the reference power predetermined for that frequency (as a correction function estimation unit). The apparatus corrects the input power at every frequency, based upon the correction coefficient that is obtained in accordance with the relation defined by the estimated correction function (as an input power correcting unit). The apparatus further determines whether or not the sound represented by the received audio signal is speech sound, based upon the corrected input power (as a speech sound detection unit).

Abstract: System and device for receiving spatially mixed signals by a plurality of sensors and accurately removing a signal from a particular direction. The system includes a beamformer for removing a signal coming from a particular direction by steering a null to the particular direction, a coefficient calculation unit for calculating a coefficient for correcting the gain of the spectrum of the signal from a sensor according to the directivity characteristic of the beamformer, a gain correction unit for correcting the signal spectrum from the sensor by the calculated correction coefficient, and a spectrum correction unit for correcting the signal spectrum outputted from the beamformer by the corrected sensor signal spectrum. A plurality of sensor signals are received and a signal from a particular direction is removed by the beamformer. The signal which has failed to be removed by the beamformer is removed by the spectrum correction unit at a later stage.

Abstract: To this end, a voice detection device includes a band-based power calculation unit that calculates a total of signal power values (sub-band power) of signals entered from the microphones from one preset frequency width (sub-band) to another. The voice detection device also includes a band-based noise estimation unit that estimates the sub-band based noise power, and a sub-band based SNR calculation unit. The sub-band based SNR calculation unit calculates a sub-band SNR from one sub-band to another to output the largest one of the sub-band SNRs as an SNR for a microphone of interest. The voice detection device further includes a voice/non-voice decision unit that determines the voice/non-voice using the SNR for the microphone of interest.

Abstract: A system for voice detection includes a feature value calculation unit that calculates a feature value from an input signal sliced on a per frame basis, a provisional voice/non-voice decision unit that provisionally decides a voiced interval and a non-voiced interval from the feature value calculated on a per frame basis, and a voice/non-voice decision unit that determines a voiced interval duration threshold value or a non-voiced interval duration threshold value, using a ratio of the feature value found on a per frame basis to a threshold value for the feature value and that re-decides the voiced interval and the non-voiced interval, using the voiced interval duration threshold value determined and the non-voiced interval duration threshold value determined.

Abstract: A voice recognition device that recognizes a voice of an input voice signal, comprises a voice model storage unit that stores in advance a predetermined voice model having a plurality of detail levels, the plurality of detail levels being information indicating a feature property of a voice for the voice model; a detail level selection unit that selects a detail level, closest to a feature property of an input voice signal, from the detail levels of the voice model stored in the voice model storage unit; and a parameter setting unit that sets parameters for recognizing the voice of an input voice according to the detail level selected by the detail level selection unit.

Abstract: Disclosed is a gain control system in which speech model constituted from a sound pressure and a feature is stored in a speech model storage unit for each of a plurality of phonemes or for each of clusters into which a speech is divided. When an input signal is given, a feature conversion unit calculates a feature and a sound pressure of the input signal. A sound pressure comparison unit determines a sound pressure ratio between the input signal and each of speech models. A distance calculation unit calculates a distance between the feature of the input signal and the feature of each of the speech models. A gain calculation unit calculates a gain value from the sound pressure ratio and information on the distance. A sound pressure compensation unit thereby compensates for the sound pressure of the input signal.

Abstract: System and device for receiving spatially mixed signals by a plurality of sensors and accurately removing a signal from a particular direction. The system includes a beamformer 1 for removing a signal coming from a particular direction by steering a null to the particular direction, a coefficient calculation unit 3 for calculating a coefficient for correcting the gain of the spectrum of the signal from a sensor M1 according to the directivity characteristic of the beamformer 1, a gain correction unit 4 for correcting the signal spectrum from the sensor M1 by the calculated correction coefficient, and a spectrum correction unit 5 for correcting the signal spectrum outputted from the beamformer 1 by the corrected sensor signal spectrum. A plurality of sensor signals are received and a signal from a particular direction is removed by the beamformer 1. The signal which has failed to be removed by the beamformer 1 is removed by the spectrum correction unit 5 at a later stage.

Abstract: Disclosed is a noise suppression system including a unit for calculating a noise mean spectrum from an input signal, a unit for deriving the provisional estimate speech from the input signal and the noise mean spectrum, a reference speech pattern, and a unit for correcting the provisional estimate speech using the reference pattern.