Integration of LDA into a telephone conversation speaker diarization system

In this work we examine whether linear discriminant analysis (LDA) can improve the diarization performance, when used as an additional phase in a telephone conversation diarization system. We first apply a classical diarization system. Using systems output (to define the classes of interest) an LDA transformation on the mel-cepstrum features is performed. Then, the final diarization process is applied onto the transformed features. A relative improvement of 14.8% was obtained on LDC America CallHome database. The LDA seemed sensible to both segment duration and amount of data available for training, as shown by the results obtained on NIST SRE-05 database where no significative improvement was observed.