Abstract: Disclosed is a method for speech speaker recognition of a speech speaker recognition apparatus, the method including detecting effective speech data from input speech; extracting an acoustic feature from the speech data; generating an acoustic feature transformation matrix from the speech data according to each of Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), mixing each of the acoustic feature transformation matrixes to construct a hybrid acoustic feature transformation matrix, and multiplying the matrix representing the acoustic feature with the hybrid acoustic feature transformation matrix to generate a final feature vector; and generating a speaker model from the final feature vector, comparing a pre-stored universal speaker model with the generated speaker model to identify the speaker, and verifying the identified speaker.

Abstract: A speaker recognition method and apparatus are provided. In the speaker recognition method, basic data and voice data of a speaker are received using contents that constantly request the speaker to constantly response using the speaker's voice. Then, a voice of the speaker is extracted from voice data, and a feature vector for recognition is extracted from the voice of the speaker. Based on the extracted feature vector, a speaker model is created. Then, a speaker stored in a speaker model is recognized based on information analyzed from input voice.

Abstract: A novel compound of the formula(I) having a high inhibitory activity against Grb2-Shc binding may be useful for the prevention and treatment of intracellular signal transmission-related diseases.