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Author Junkawitsch, J. ♦ Neubauer, L. ♦ Höge, H. ♦ Ruske, G.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Speech Recognition ♦ Hmm-based Keyword Spotting System ♦ First Discussion Topic ♦ Keyword Spotting ♦ New Keyword Spotting Algorithm ♦ Keyword Specific Decision Threshold ♦ Non-keyword Part ♦ Low Computional Expense ♦ New Algorithm ♦ Viterbi Algorithm ♦ Storage Requirement ♦ Optimal Decision Threshold ♦ Promising Branch ♦ Hmm Score ♦ Speech Signal ♦ Keyword Hmms ♦ Search Algorithm ♦ Garbage Model ♦ Pre-calculated Optimal Threshold ♦ Second Discussion Topic ♦ Decision Threshold
Description Keyword spotting is a very forward-looking and promising branch of speech recognition. This 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 computional expense and storage requirement. The second discussion topic is the determination of a optimal decision threshold for each keyword. In order two 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. This paper introduces a method to fix decision thresholds in advance. Starting...
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1996-01-01
Publisher Institution ICSLP 96, Philadelphia