Efficient speaker identification and retrieval

Hagai Aronowitz*, David Burshtein

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

7 Scopus citations


In this paper we present techniques for efficient speaker recognition of a large population of speakers and for efficient speaker retrieval in large audio archives. We deal with aspects of both time and storage. We use Gaussian mixture modeling (GMM) for representing both train and test sessions and show how to perform speaker recognition and retrieval efficiently with only a small degradation in accuracy compared to classic GMM based recognition. We present techniques for achieving a dramatic acceleration of both tasks. Finally, we present a GMM compression algorithm that decreases considerably the storage needed for speaker retrieval.

Original languageEnglish
Number of pages4
StatePublished - 2005
Event9th European Conference on Speech Communication and Technology - Lisbon, Portugal
Duration: 4 Sep 20058 Sep 2005


Conference9th European Conference on Speech Communication and Technology


Dive into the research topics of 'Efficient speaker identification and retrieval'. Together they form a unique fingerprint.

Cite this