NDLI: Direct posterior confidence for out-of-vocabulary spoken term detection

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Direct posterior confidence for out-of-vocabulary spoken term detection

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Direct posterior confidence for out-of-vocabulary spoken term detection

Content Provider	ACM Digital Library
Author	Vipperla, Ravichander Evans, Nicholas Frankel, Joe Troncy, Raphaël Wang, Dong King, Simon
Copyright Year	2012
Abstract	Spoken term detection (STD) is a key technology for spoken information retrieval. As compared to the conventional speech transcription and keyword spotting, STD is an open-vocabulary task and has to address out-of-vocabulary (OOV) terms. Approaches based on subword units, for example phones, are widely used to solve the OOV issue; however, performance on OOV terms is still substantially inferior to that of in-vocabulary (INV) terms. The performance degradation on OOV terms can be attributed to a multitude of factors. One particular factor we address in this article is the unreliable confidence estimation caused by weak acoustic and language modeling due to the absence of OOV terms in the training corpora. We propose a direct posterior confidence derived from a discriminative model, such as multilayer perceptron (MLP). The new confidence considers a wide-range acoustic context which is usually important for speech recognition and retrieval; moreover, it localizes on detected speech segments and therefore avoids the impact of long-span word context which is usually unreliable for OOV term detection. In this article, we first develop an extensive discussion about the modeling weakness problem associated with OOV terms, and then propose our approach to address this problem based on direct poster confidence. Our experiments carried out on spontaneous and conversational multiparty meeting speech, demonstrate that the proposed technique provides a significant improvement in STD performance as compared to conventional lattice-based confidence, in particular for OOV terms. Furthermore, the new confidence estimation approach is fused with other advanced techniques for OOV treatment, such as stochastic pronunciation modeling and discriminative confidence normalization. This leads to an integrated solution for OOV term detection that results in a large performance improvement.
Starting Page	1
Ending Page	34
Page Count	34
File Format	PDF
ISSN	10468188
e-ISSN	15582868
DOI	10.1145/2328967.2328969
Volume Number	30
Issue Number	3
Journal	ACM Transactions on Information Systems (TOIS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-09-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Speech recognition Spoken term detection Spontaneous speech search
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Information Systems Business, Management and Accounting

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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Direct posterior confidence for out-of-vocabulary spoken term detection

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