Speaker diarization is an important problem that is topical, and is especially useful as a
preprocessor for conversational speech related applications. The objective of this article is …

Collecting training data for real-world text-independent speaker recognition is challenging.
In practice, utterances for a specific speaker are often mixed with many other acoustic …

Many state-of-the-art diarization systems for meeting recordings are based on the
HMM/GMM framework and the combination of spectral (MFCC) and time delay of arrivals …

The two-pass information bottleneck (TPIB) based speaker diarization system operates
independently on different conversational recordings. TPIB system does not consider …

In this thesis we investigate a non parametric approach to speaker diarization for meeting
recordings based on an information theoretic framework. The problem is formulated using …

Speaker diarization for meetings data are recently converging towards multistream systems.
The most common complementary features used in combination with MFCC are Time Delay …

An approach to diarize taniavartanam segments of a Carnatic music concert is proposed in
this paper. Information bottleneck (IB) based approach used for speaker diarization is …

Speaker diarization of meetings recorded with Multiple Distant Microphones makes
extensive use of multiple feature streams like MFCC and Time Delay of Arrivals (TDOA) …

Instrument separation in an ensemble is a challenging task. In this work, we address the
problem of separating the percussive voices in the taniavartanam segments of Carnatic …

Multistream diarization is an effective way to improve the diarization performance, MFCC
and Time Delay Of Arrivals (TDOA) being the most commonly used features. This paper …