Extraction of speaker-specific features from spoken code sentences

In the speaker-verification task speakers are assumed to be cooperative and are therefore willing to pronounce a pre-arranged code sentence. This paper deals with the extraction of speaker-specific features from a time-normalized parametric description of the code sentence. A new mml (minimum-maximum-locating) method for time-normalization is presented together with an overview of techniques used for feature-extraction. Results of recognition experiments are discussed, which have been obtained with the AUROS system (Automatic Recognition of Speakers by Computers).