Speaker Identification Using Instantaneous Frequencies

This work presents an experimental evaluation of different features for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus, in a closed set speaker identification task. The main objective of the paper is to present a novel parametrization of speech that is based on the AM-FM representation of the speech signal and to assess the utility of these features in the context of speaker identification. In order to explore the extent to which different instantaneous frequencies due to the presence of formants and harmonics in the speech signal may predict a speaker's identity, this work evaluates three different decompositions of the speech signal within the same AM-FM framework: a first setup has been used previously for formant tracking; a second setup is designed to enhance familiar resonances below 4000 Hz, and a third setup is designed to approximate the bandwidth scaling of the filters conventionally used in the extraction of MFCCs....

• Type: Journal
• Year: 2008
• Where: TASLP
• Authors: Marco Grimaldi, Fred Cummins
• Keywords: Speaker Identification, Speaker Identification Task, Speech Signal, TASLP 2008