NDLI: i-Vector modeling of speech attributes for automatic foreign accent recognition

Content Provider	ACM Digital Library
Author	Lee, Chin-Hui Siniscalchi, Sabato Marco Kinnunen, Tomi Behravan, Hamid Hautamäki, Ville
Copyright Year	2016
Abstract	We propose a unified approach to automatic foreign accent recognition. It takes advantage of recent technology advances in both linguistics and acoustics based modeling techniques in automatic speech recognition (ASR) while overcoming the issue of a lack of a large set of transcribed data often required in designing state-of-the-art ASR systems. The key idea lies in defining a common set of fundamental units "universally" across all spoken accents such that any given spoken utterance can be transcribed with this set of "accent-universal" units. In this study, we adopt a set of units describing manner and place of articulation as speech attributes. These units exist in most spoken languages and they can be reliably modeled and extracted to represent foreign accent cues. We also propose an i-vector representation strategy to model the feature streams formed by concatenating these units. Testing on both the Finnish national foreign language certificate (FSD) corpus and the English NIST 2008 SRE corpus, the experimental results with the proposed approach demonstrate a significant system performance improvement with p-value < 0.05 over those with the conventional spectrum-based techniques. We observed up to a 15% relative error reduction over the already very strong i-vector accented recognition system when only manner information is used. Additional improvement is obtained by adding place of articulation clues along with context information. Furthermore, diagnostic information provided by the proposed approach can be useful to the designers to further enhance the system performance.
Starting Page	29
Ending Page	41
Page Count	13
File Format	PDF
ISSN	23299290
e-ISSN	23299304
DOI	10.1109/TASLP.2015.2489558
Volume Number	24
Issue Number	1
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-01-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Attribute detectors English corpus Finnish corpus I-vector system
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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
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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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