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 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: 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.