Abstract:
PURPOSE: A Corpus-based language model discrimination learning method and a device thereof are provided to easily build and use a learning database corresponding to a target domain by building a discrimination learning training corpus database with a text corpus. CONSTITUTION: A language model discrimination learning database extracts a voice feature vector from a corpus database to be built(S302). Continuous speech voice recognition is performed by receiving the voice feature vector(S303). The language model discrimination learning is performed by using a score sentence score and a voice recognition result outputted through continuous speech voice recognition performance(S304). A discrimination language model is generated(S305). [Reference numerals] (AA) Start; (BB) End; (S301) Build a DB for language model discrimination learning; (S302) Extract a voice feature vector; (S303) Recognize voice of continuous speech; (S304) Perform the language model discrimination learning; (S305) Generate a discriminative language model
Abstract:
PURPOSE: A confusion network rescoring device for Korean continuous voice recognition, a method for generating a confusion network by using the same, and a rescoring method thereof are provided to improve a generation speed of the confusion network by setting a limit of a lattice link probability in a process for converting a lattice structure into a confusion network structure. CONSTITUTION: A confusion network rescoring device receives on or more lattices generated through voice recognition(S105). The device calculates each posterior probability of the lattices(S110). The device allocates a node included in the lattices to plural equivalence classes based on the posterior probability(S120,S130,S135). The device generates a confusion set by using the equivalence classes(S150,S155). The device generates a confusion network based on the confusion set. [Reference numerals] (AA) Start; (BB,DD,FF,HH,JJ) No; (CC,EE,GG,II,KK) Yes; (LL) End; (S105) Inputting lattices through voice recognition; (S110) Calculating each posterior probability of the lattices; (S115) Inputting SLF?; (S120) Allocating a first node(no) of the lattices to a first equivalence class(NO); (S125) N_i and n_i links exist?; (S130) Allocating an i-th node(n_i) of the lattices to a j-th equivalence class(N_j); (S135) Allocating the i-th node(n_i) of the lattices to a i-th equivalence class(N_i); (S140) Allocating all nodes of the lattices?; (S145) If u∈N_s n_i∈N_t, t=s+1 in e(u->n_i); (S150) Classifying the e(u->n_i) as CS(N_s,N_t); (S155) Classifying the e(u->n_i) as CS(N_k,N_k+1); (S160) Normalizing link probability in an extracted CS sequence; (S165) Adding a Null link, and allocating remaining probability values of a normalized value; (S170) Possibility value of the Null link > possibility value of the other link; (S175) Excluding the CS sequence from a voice recognition result
Abstract:
PURPOSE: A voice recognition apparatus and a method thereof are provided to increase recognition speed of an input signal and to perform recognition of an input signal in parallel. CONSTITUTION: A global database unit(10) includes a global feature vector(12), a global vocabulary model(14), and a global sound model(16). A recognition unit(20) includes separated recognition units(22a~22n). A plurality of separate recognition units performs voice recognition in parallel. A separate database unit(30) includes separate language models. A collection and evaluation unit(40) collects and evaluates the recognition result of the separate recognition unit.
Abstract:
본발명은캡스트럼평균차감방법및 그장치에관한것으로, 온라인음성인식서비스에서묵음구간의캡스트럼평균값을사용하여실제음성구간전체의캡스트럼평균값을추정함으로써, 채널특성을보다정확하게정규화할수 있다. 또한, 본발명은주변환경변화가발생하는경우에대해서도정확한캡스트럼평균값을추정할수 있어채널정규화성능이우수하다. 또한, 본발명은온라인음성인식상황에서추정하는묵음구간의캡스트럼평균값과실제음성구간전체의캡스트럼평균값과의차이로인한음성인식성능저하를극복할수 있다.
Abstract:
PURPOSE: An international interpretation device and method thereof based on voice recognition are provided to supply text data or a synthetic voice which is interpreted in a native language to attendees. CONSTITUTION: A conference participant information registering unit(100) registers conference participant information including the language used by a conference participant. A voice recognition unit(200) registers a keyword according to the conference participant contents of presentations in advance. The voice recognition circuit outputs a voice recognition result of a keyword form. A language interpreting unit(300) performs conversion to a target language corresponding to a using language per conference participants.
Abstract:
PURPOSE: A passive optical scriber network system of a wavelength division multiplexing is provided to compensate a penalty by deterioration according a signal mode optical fiber transmission itself. CONSTITUTION: An OLT(Optical Line Terminal)(100) multiplexes the spectrum-divided light per wavelength after diving spectrum of the wideband non-interference light. The ONT(Optical Network Terminal)(200) receives an optical signal from the OLT. A remote node connects the OLT and the ONT. By using dispersion compensation fiber, a dispersion compensation module(170) compensates a relative intensity noise.
Abstract:
PURPOSE: A location tracing apparatus using user voice and method thereof are provided to reduce voice recognition degradation by echo sound and to integrate a sound source location determination technology. CONSTITUTION: A sound source determining unit(10) divides two channel signals by sound source. A stereo wiener filter unit(20) removes a noise from a sound source signal that is separated by the sound source determining unit. The stereo wiener filter unit filters a residual signal factor. A voice recognition unit(60) recognizes the voice of a user from the separated sound source signal and measures the reliability for a voice recognition result. A channel select unit(80) selects a target channel based on the reliability for the voice recognition result. A sound source location tracing unit(130) analyzes an interfere channel signal and a target channel signal.
Abstract:
PURPOSE: An apparatus and a method for detecting optical signal are provided to use determination threshold value which optimized by the received signal. CONSTITUTION: An optical signal detection apparatus comprises a signal receiving part(210) for changing the received optical signal into the electric signal, and a signal detection(230) for detecting the transformed electric signal based on the optimized determination threshold value calculating. The determination threshold value decision unit establishes the mathematical model based on the transformed electric signal.