Abstract: A recognition confidence measurement method, medium and system which can more accurately determine whether an input speech signal is an in-vocabulary, by extracting an optimum number of candidates that match a phone string extracted from the input speech signal and estimating a lexical distance between the extracted candidates is provided. A recognition confidence measurement method includes: extracting a phoneme string from a feature vector of an input speech signal; extracting candidates by matching the extracted phoneme string and phoneme strings of vocabularies registered in a predetermined dictionary and; estimating a lexical distance between the extracted candidates; and determining whether the input speech signal is an in-vocabulary, based on the lexical distance.

Abstract: An apparatus for speech recognition includes: a first confidence score calculator calculating a first confidence score using a ratio between a likelihood of a keyword model for feature vectors per frame of a speech signal and a likelihood of a Filler model for the feature vectors; a second confidence score calculator calculating a second confidence score by comparing a Gaussian distribution trace of the keyword model per frame of the speech signal with a Gaussian distribution trace sample of a stored corresponding keyword of the keyword model; and a determination module determining a confidence of a result using the keyword model in accordance with a position determined by the first and second confidence scores on a confidence coordinate system.

Abstract: Disclosed herein is a method and apparatus to recognize speech by measuring the confidence levels of respective frames. The method includes the operations of obtaining frequency features of a received speech signal for the respective frames having a predetermined length, calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frame, calculating a confidence score based on the two types of likelihoods, and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on the confidence scores. Also, the method includes the operation of transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores.

Abstract: A method of searching music using speech recognition in a mobile device, the method including: recognizing a speech signal uttered by a user as a phoneme sequence; and searching music information by performing partial symbol matching between the recognized phoneme sequence and a standard pronunciation sequence.

Abstract: An apparatus and method for recognizing voice.

Abstract: A method and an apparatus for selecting a vocabulary closest to an input speech from among lexicons stored in memory, wherein a centroid lexicon representing lexicons belonging to a predetermined lexicon group is generated. Two lexicons, having a longest distance therebetween in the lexicon group, are selected using the centroid lexicon from the lexicon group, and a node indicating the lexicon group branches based on the two selected lexicons. A node having low group similarity is selected from among current terminal nodes, including branch nodes, and the above procedure is repeatedly performed on a lexicon group indicated by the selected node.

Abstract: An apparatus for reducing a noise signal of a speech signal in a speech recognizer, the apparatus estimating a signal to noise ratio for each frequency band of the speech signal, applying a noise suppression rate based on the estimated signal to noise ratio, and reducing the noise signal of the speech signal.

Abstract: A speech recognition method including: layering a central lexicon in a tree structure with respect to recognition-subject vocabularies; performing multi-pass symbol matching between a recognized phoneme sequence and a phonetic sequence of the central lexicon layered in the tree structure; and selecting a final speech recognition result via a Viterbi search process using a detailed acoustic model with respect to candidate vocabularies selected by the multi-pass symbol matching.

Abstract: A method of searching music using speech recognition in a mobile device, the method including: recognizing a speech signal uttered by a user as a phoneme sequence; and searching music information by performing partial symbol matching between the recognized phoneme sequence and a standard pronunciation sequence.

Abstract: A speech recognition method including: layering a central lexicon in a tree structure with respect to recognition-subject vocabularies; performing multi-pass symbol matching between a recognized phoneme sequence and a phonetic sequence of the central lexicon layered in the tree structure; and selecting a final speech recognition result via a Viterbi search process using a detailed acoustic model with respect to candidate vocabularies selected by the multi-pass symbol matching.

Abstract: A recognition confidence measurement method, medium and system which can more accurately determine whether an input speech signal is an in-vocabulary, by extracting an optimum number of candidates that match a phone string extracted from the input speech signal and estimating a lexical distance between the extracted candidates is provided. A recognition confidence measurement method includes: extracting a phoneme string from a feature vector of an input speech signal; extracting candidates by matching the extracted phoneme string and phoneme strings of vocabularies registered in a predetermined dictionary and; estimating a lexical distance between the extracted candidates; and determining whether the input speech signal is an in-vocabulary, based on the lexical distance.

Abstract: An apparatus for speech recognition includes: a first confidence score calculator calculating a first confidence score using a ratio between a likelihood of a keyword model for feature vectors per frame of a speech signal and a likelihood of a Filler model for the feature vectors; a second confidence score calculator calculating a second confidence score by comparing a Gaussian distribution trace of the keyword model per frame of the speech signal with a Gaussian distribution trace sample of a stored corresponding keyword of the keyword model; and a determination module determining a confidence of a result using the keyword model in accordance with a position determined by the first and second confidence scores on a confidence coordinate system.

Abstract: An apparatus and method for recognizing voice.

Abstract: Disclosed herein is a method and apparatus to recognize speech by measuring the confidence levels of respective frames. The method includes the operations of obtaining frequency features of a received speech signal for the respective frames having a predetermined length, calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frame, calculating a confidence score based on the two types of likelihoods, and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on the confidence scores. Also, the method includes the operation of transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores.

Abstract: A method and an apparatus for selecting a vocabulary closest to an input speech from among lexicons stored in memory, wherein a centroid lexicon representing lexicons belonging to a predetermined lexicon group is generated. Two lexicons, having a longest distance therebetween in the lexicon group, are selected using the centroid lexicon from the lexicon group, and a node indicating the lexicon group branches based on the two selected lexicons. A node having low group similarity is selected from among current terminal nodes, including branch nodes, and the above procedure is repeatedly performed on a lexicon group indicated by the selected node.