Abstract: Provided are a multi-stage speech recognition apparatus and method. The multi-stage speech recognition apparatus includes a first speech recognition unit performing initial speech recognition on a feature vector, which is extracted from an input speech signal, and generating a plurality of candidate words; and a second speech recognition unit rescoring the candidate words, which are provided by the first speech recognition unit, using a temporal posterior feature vector extracted from the speech signal.

Abstract: Provided are a distributed speech recognition system, a distributed speech recognition speech method, and a terminal and a server for distributed speech recognition. The distributed speech recognition system includes a terminal which decodes a feature vector that is extracted from an input speech signal into a sequence of phonemes and generates the final recognition result by rescoring a candidate list provided from the outside; and a server which generates the candidate list by performing symbol matching on the recognized sequence of phonemes provided from the terminal and transmits the candidate list for the rescoring to the terminal.

Abstract: A method and apparatus for improving the performance of voice recognition in a mobile device are provided. The method of recognizing a voice includes: monitoring the usage pattern of a user of a device for inputting a voice; selecting predetermined words from among words stored in the device based on the result of monitoring, and storing the selected words; and recognizing a voice based on an acoustic model and predetermined words. In this way, a voice can be recognized by using prediction of whom the user mainly makes a call to. Also, by automatically modeling the device usage pattern of the user and applying the pattern to vocabulary for voice recognition based on probabilities, the performance of voice recognition, as actually felt by the user, can be enhanced.

Abstract: Provided is a method and apparatus for transforming a speech feature vector. The method includes extracting a feature vector required for speech recognition from a speech signal and transforming the extracted feature vector using an auto-associative neural network (AANN).

Abstract: A speech synthesis method, in which speech units are concatenated using a DB, wherein the speech units to be concatenated are determined and divided into a left speech unit and a right speech unit. The length of an interpolation region of each of the left and right speech units is variably determined. An extension is attached to a right boundary of the left speech unit and an extension to a left boundary of the right speech unit. The locations of pitch marks included in the extension of each of the left and right speech units are aligned so that the pitch marks can fit in the predetermined interpolation region. The left and right speech units are superimposed after fading out the left speech unit and fading in the right speech unit. Accordingly, a determination of whether extra-segmental data exists or not is made, and smoothing concatenation is performed using either an interpolation of existing data or an interpolation of extrapolated data depending on the result of the determination.

Abstract: A flexible printed circuit board includes a first substrate portion having at least one first terminal, a second substrate portion in communication with the first substrate portion and having at least one circuit device, a connection substrate portion in communication with the second substrate portion, the connection substrate portion extending away from the second substrate portion in a same direction as the first substrate portion, and a third substrate portion in communication with the connection substrate portion, the third substrate portion having at least one second terminal.

Abstract: A mobile information retrieval method, clustering method, and an information retrieval system using a user's search history. The mobile information retrieval method includes receiving the user's query information and retrieving information related to the query information through predetermined networks in a database in which history information generated by previous retrieval is stored. The mobile information retrieval method, clustering method, and information retrieval system can relieve inconvenience of information retrieval caused by limits in terms of a display screen, battery capacity and computing resources, and can curtail charges for Internet use and data downloads.

Abstract: A speech synthesis system for controlling a discontinuous distortion that occurs at the transition portion between concatenated phonemes which are speech units of a synthesized speech using a smoothing technique, comprising: a discontinuous distortion processing means adapted to predict a discontinuity at the transition portion between concatenated samples of phonemes used for a speech synthesis through a predetermined learning process, and control a discontinuity at the transition portion between the concatenated phonemes of the synthesized speech in such a fashion that it is smoothed adaptively to correspond to a degree of the predicted discontinuity. The smoothing filter smoothes the synthesized speech so that the discontinuity degree of synthesized speech follows the predicted discontinuity degree according to the filter coefficient (a) changed adaptively to correspond to a ratio of the predicted discontinuity degree to the real discontinuity degree.

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: There are provided a system and method for providing information using a spoken dialogue interface. The system includes a speech recognizer for transforming voice signals into sentences; a sentence analyzer for analyzing the sentences by their structural elements; a dialogue manager for extracting information on speech acts or intentions from the structural elements, and generating information on system's speech acts or intentions for a response to the extracted information on speech acts or intentions; a sentence generator for generating sentences based on the information on the system's speech acts or intentions for the response; a speech synthesizer for synthesizing the generated sentences into voices; an information extractor for extracting information required for the response from the Internet in real time; and a user modeling means for analyzing and classifying users' tendencies.

Abstract: An apparatus and method for detecting a named-entity. The apparatus includes a candidate-named-entity extraction module that detects a candidate-named-entity based on an initial learning example and feature information regarding morphemes constituting an inputted sentence, the candidate-named-entity extraction module providing a tagged sentence including the detected candidate-named-entity; a storage module that stores information regarding a named-entity dictionary and a rule; and a learning-example-regeneration module for finally determining whether the candidate-named-entity included in the provided sentence is a valid named-entity, based on the named-entity dictionary and the rule, the learning-example-regeneration module providing the sentence as a learning example, based on a determination result, so that a probability of candidate-named-entity detection is gradually updated.

Abstract: An apparatus and method for recognizing voice.

Abstract: An apparatus and method for detecting a voice activity period. The apparatus for detecting a voice activity period includes a domain conversion module that converts an input signal into a frequency domain signal in the unit of a frame obtained by dividing the input signal at predetermined intervals, a subtracted-spectrum-generation module that generates a spectral subtraction signal which is obtained by subtracting a predetermined noise spectrum from the converted frequency domain signal, a modeling module that applies the spectral subtraction signal to a predetermined probability distribution model, and a speech-detection module that determines whether a speech signal is present in a current frame through a probability distribution calculated by the modeling module.

Abstract: An apparatus, medium, and method providing audio files with clustering, with audio files having information similar to queries input from a user being extracted and undergo clustering. A method for providing audio files with clustering includes calculating scores between queries input from a user and a specified audio file, detecting audio files having specified scores with the queries input from the user on the basis of the result of calculation and performing a dynamic clustering of the audio files, detecting the audio files having the specified scores with the queries input from the user and performing a static clustering of the audio files, and displaying the dynamic cluster or the static cluster on a screen.

Abstract: A user adaptive speech recognition method and apparatus is disclosed that controls user confirmation of a recognition candidate using a new threshold value adapted to a user. The user adaptive speech recognition method includes calculating a confidence score of a recognition candidate according to the result of speech recognition, setting a new threshold value adapted to the user based on a result of user confirmation of the recognition candidate and the confidence score of the recognition candidate, and outputting a corresponding recognition candidate as a result of the speech recognition if the calculated confidence score is higher than the new threshold value. Thus, the need for user confirmation of the result of speech recognition is reduced and the probability of speech recognition success is increased.

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.

Abstract: A speech recognition method and apparatus and a navigation system having the speech recognition apparatus are provided. The speech recognition method includes capturing speech as speech signal and extracting features from the speech signal, selecting candidates of a subword among subwords of the word based on the extracted features and displaying the candidate subwords for the subword, selecting candidates of a next subword following the subword based on the selected candidates of the subword and displaying the candidates of the next subword, and determining whether the user has selected one of the candidates of the next subword and, if not, selecting candidates of subwords following the next subword based on the series of subwords that have been previously selected by the user and displaying the selected candidates of the next subword.

Abstract: The present invention relates to pyridine sulfonyl urea derivatives, salts or stereochemical isomers thereof showing an effective herbicidal activity in pre- and/or post-emergence treatment in rice farming, or to a method to use thereof, a method for the preparation thereof, an intermediate used for the preparation thereof, and a herbicidal composition comprising same.

Abstract: A method of automatic labeling using an optimum-partitioned classified neural network includes searching for neural networks having minimum errors with respect to a number of L phoneme combinations from a number of K neural network combinations generated at an initial stage or updated, updating weights during learning of the K neural networks by K phoneme combination groups searched with the same neural networks, and composing an optimum-partitioned classified neural network combination using the K neural networks of which a total error sum has converged; and tuning a phoneme boundary of a first label file by using the phoneme combination group classification result and the optimum-partitioned classified neural network combination, and generating a final label file reflecting the tuning result.