Personal tools
You are here: Home → Knowledge Base → Speaker Clustering via Bayesian Information Criterion using a Global Similarity Constraint  

Speaker Clustering via Bayesian Information Criterion using a Global Similarity Constraint

Main information
In this paper we proposed a global similarity constraint that improves speaker clustering as standardly performed using the Bayesian Information Criterion (BIC). The novelty of our approach lies in the fact that it exploits the hypothesis that audio segments belonging to the same speaker cluster should demonstrate similar global behavior, i.e. exhibit approximately the same pattern of similarity and dissimilarity with the all other segments. Every segment is represented by a global similarity vector whose components encode the BIC-based local similarity between that segment and each of the other segments to be clustered. Speaker clustering is performed bottom up using the BIC to compare each pair of segments and determine if their similarity is high enough to merge them. We use the global similarity vectors to constrain merging to segment pairs that have approximately the same patterns of global similarity. The evaluation, performed on audio data from 4 different German-language radio programs, shows that the proposed approach represents an improvement on the standard BIC clustering. 
WP5: Detection, Extraction and Annotation of Knowledge. 
IAIS  Konstantin Biatov, Martha Larson 
2007-03-15 17:38  Request for more detail


Access and Use Rights
Condition of use defined in response to "need to access request". 
Copyright Fraunhofer Institut Intelligente Analyse- und Informationssysteme. 
 
Closed, attachment is not public 


This item is not available for public download. For further information click on Request for more details above

LIVE's knowledge base
  • What is available here?

Here you can search and access the documented work of the LIVE project. Documents include the official reporting of the project's work known as "deliverables", scientific and technical publications, study reports, press material, presentation material  as well as IPR pending material.

  • How can I access the material?

You can search this knowledge base by project partner, work area or key words.

By simply clicking "all" the complete list of documents will be listed.

  • Is everything open to the public?

Please note that only those publications marked in green have been cleared for immediate public access. To request access to those publications not open please click on the "request for more detail" link in the relevant document. Your request will be automatically sent to the authors for consideration.