10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Exploring Universal Attribute Characterization of Spoken Languages for Spoken Language Recognition

Sabato Marco Siniscalchi (1), Jeremy Reed (2), Torbjørn Svendsen (1), Chin-Hui Lee (2)

(1) NTNU, Norway
(2) Georgia Institute of Technology, USA

We propose a novel universal acoustic characterization approach to spoken language identification (LID), in which any spoken language is described with a common set of fundamental units defined “universally.” Specifically, manner and place of articulation form this unit inventory and are used to build a set of universal attribute models with data-driven techniques. Using the vector space modeling approaches to LID a spoken utterance is first decoded into a sequence of attributes. Then, a feature vector consisting of co-occurrence statistics of attribute units is created, and the final LID decision is implemented with a set of vector space language classifiers. Although the present study is just in its preliminary stage, promising results comparable to acoustically rich phone-based LID systems have already been obtained on the NIST 2003 LID task. The results provide clear insight for further performance improvements and encourage a continuing exploration of the proposed framework.

Full Paper

Bibliographic reference.  Siniscalchi, Sabato Marco / Reed, Jeremy / Svendsen, Torbjørn / Lee, Chin-Hui (2009): "Exploring universal attribute characterization of spoken languages for spoken language recognition", In INTERSPEECH-2009, 168-171.