摘要:
Disclosed herein is an apparatus and method for creating an acoustic model. The apparatus includes a binary tree creation unit, an information creation unit, and a binary tree reduction unit. The binary tree creation unit creates a binary tree by repeatedly merging a plurality of Gaussian components for each Hidden Markov Model (HMM) state of an acoustic model based on a distance measure reflecting a variation in likelihood score. The information creation unit creates information about information about the largest size of the acoustic model in accordance with a platform including a speech recognizer. The binary tree reduction unit reduces the binary tree in accordance with the information about the largest size of the acoustic model.
摘要:
An apparatus for a speech recognition based on source separation and identification includes: a sound source separator for separating mixed signals, which are input to two or more microphones, into sound source signals by using independent component analysis (ICA), and estimating direction information of the separated sound source signals; and a speech recognizer for calculating normalized log likelihood probabilities of the separated sound source signals. The apparatus further includes a speech signal identifier identifying a sound source corresponding to a user's speech signal by using both of the estimated direction information and the reliability information based on the normalized log likelihood probabilities.
摘要:
An apparatus for evaluating the performance of speech recognition includes a speech database for storing N-number of test speech signals for evaluation. A speech recognizer is located in an actual environment and executes the speech recognition of the test speech signals reproduced using a loud speaker from the speech database in the actual environment to produce speech recognition results. A performance evaluation module evaluates the performance of the speech recognition by comparing correct recognition results answers with the speech recognition results.