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.

S. M. SINISCALCHI, J. REED, T. SVENDSEN, AND C.-H. LEE (2009). Exploring Universal Attribute Characterization of Spoken Languages for Spoken Language Recognition. In INTERSPEECH 2009 (pp. 168-171). ISCA-INST SPEECH COMMUNICATION ASSOC, C/O EMMANUELLE FOXONET, 4 RUE DES FAUVETTES, LIEU DIT LOUS TOURILS [10.21437/Interspeech.2009-67].

Exploring Universal Attribute Characterization of Spoken Languages for Spoken Language Recognition

S. M. SINISCALCHI;
2009-01-01

Abstract

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.
2009
Settore IINF-05/A - Sistemi di elaborazione delle informazioni
978-1-61567-692-7
S. M. SINISCALCHI, J. REED, T. SVENDSEN, AND C.-H. LEE (2009). Exploring Universal Attribute Characterization of Spoken Languages for Spoken Language Recognition. In INTERSPEECH 2009 (pp. 168-171). ISCA-INST SPEECH COMMUNICATION ASSOC, C/O EMMANUELLE FOXONET, 4 RUE DES FAUVETTES, LIEU DIT LOUS TOURILS [10.21437/Interspeech.2009-67].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/663739
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