Abstract: A voice recognition apparatus includes an extraction unit extracting a feature amount from a voice signal, a word dictionary storing a plurality of recognition words; a reject word generation unit storing reject words in the word dictionary in association with the recognition words and a collation unit calculating a degree of similarity between the voice signal and each of the recognition words and reject words stored in the word dictionary by using the feature amount extracted by the extraction unit, determining whether or not a word having a high calculated degree of similarity corresponds to a reject word, when the word is determined as the reject word, excluding the recognition word stored in the word dictionary in association with the reject word from a result of recognition, and outputting a recognition word having a high calculated degree of similarity as a result of recognition.

Abstract: A speech recognition system includes the following: a feature calculating unit; a sound level calculating unit that calculates an input sound level in each frame; a decoding unit that matches the feature of each frame with an acoustic model and a linguistic model, and outputs a recognized word sequence; a start-point detector that determines a start frame of a speech section based on a reference value; an end-point detector that determines an end frame of the speech section based on a reference value; and a reference value updating unit that updates the reference value in accordance with variations in the input sound level. The start-point detector updates the start frame every time the reference value is updated. The decoding unit starts matching before being notified of the end frame and corrects the matching results every time it is notified of the start frame. The speech recognition system can suppress a delay in response time while performing speech recognition based on a proper speech section.

Abstract: When the degree of similarity of the recognition candidates is greater than the second threshold value, the speech verification unit outputs the recognition candidates as a recognition result, and when the degree of similarity of the recognition candidates is smaller than the second threshold value, it outputs the recognition candidates as a recognition result if the degree of similarity of the recognition candidates is greater than the first threshold value and, at the same time, the degree of similarity of the recognition candidates is greater than the degree of similarity of the rejection candidates. It should be noted that the first threshold value is a measure used for rejecting input speech. The second threshold value is larger than the first threshold value and is used as a measure for outputting recognition candidates as a recognition result.

Abstract: A speech recognition apparatus for recognizing a plurality of sequential words contained in a speech includes an acoustic model reading part for reading an acoustic model, a dictionary management part for reading required data from dictionary data, and a recognition part for successively recognizing the sequential words by matching a group of words represented by the dictionary data with the inputted speech, using the acoustic model, wherein the dictionary data contains a beginning part dictionary representing beginning parts of words, and a group of ending part dictionaries storing data representing ending parts, the ending part dictionary and/or the beginning part dictionary are read in accordance with the word recognized by the recognition part, and the recognition part matches a subsequent speech with the beginning parts of words contained in the beginning part dictionary while the dictionary management part is reading the ending part dictionary and/or the beginning part dictionary.

Abstract: A voice recognition system and a voice processing system in which a self-repair utterance can be inputted and recognized accurately as in a conversation between humans in the case where a user makes the self-repair utterance are provided. An signal processing unit for converting speech voice data into a feature, a voice section detecting unit for detecting voice sections in the speech voice data, a priority determining unit for selecting a voice section to be given priority from among the voice sections detected by the voice section detecting unit according to a predetermined priority criterion, and a decoder for calculating a degree of matching with a recognition vocabulary using the feature of the voice section selected by the priority determining unit and an acoustic model are included.

Abstract: Text data describing the contents of an uttered voice and voice data uttered by a user corresponding to the text data are stored as a pair of data. Text data and voice data are input, and recognition results peculiar to a user are learned before start-up based on a pair of the text data and the voice data, whereby a user-specific acoustic model or a user-specific filter is generated.

Abstract: A process for producing silver-coated potassium titanate fibers comprises admixing the potassium titanate fibers with a silver ion solution containing a reducing agent. The resulting silver-coated potassium titanate fibers can, if desired, be provided with one or more additional metal coatings superimposed on the silver coat wherein the additional metal is other than silver.