NDLI: A new keyword spotting algorithm with pre-calculated optimal thresholds

Content Provider	IEEE Xplore Digital Library
Author	Junkawitsch, J. Neubauer, L. Hoge, H. Ruske, G.
Copyright Year	1996
Description	Author affiliation: Tech. Univ. Munchen, Germany (Junkawitsch, J.)
Abstract	Keyword spotting is a very forward looking and promising branch of speech recognition. The paper presents a HMM based keyword spotting system, which works with a new algorithm. The first discussion topic is the description of the search algorithm, that needs no representation of the non keyword parts of the speech signal. For this purpose, the computation of the HMM scores and the Viterbi algorithm had to be modified. The keyword HMMs are not concatenated with other HMMs, so that there is no necessity for filler or garbage models. As a further advantage, this algorithm needs only low computational expense and storage requirement. The second discussion topic is the determination of a optimal decision threshold for each keyword. In order to decide between the two possibilities "keyword was spoken" and "keyword was not spoken", the scores of the keywords are compared with keyword specific decision thresholds. The paper introduces a method to fix decision thresholds in advance. Starting with measured phoneme distributions, the score distributions of whole keyword models can be calculated. Furthermore, these keyword distributions form the basis of the computation of decision thresholds. Tests with spontaneous speech databases yielded 73.9% Figure Of Merit when using context dependent HMMs. The detection rate at 10 fa/kw/h comes to 80%.
Starting Page	2067
Ending Page	2070
File Size	404131
Page Count	4
File Format	PDF
ISBN	0780335554
DOI	10.1109/ICSLP.1996.607208
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-10-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Viterbi algorithm Databases Convolution Acoustic noise Hidden Markov models Speech recognition Gaussian distribution Concatenated codes Distributed computing Testing
Content Type	Text
Resource Type	Article

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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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