A New Framework For Large Vocabulary Keyword Spotting Using Two-Pass Confidence Measure

2006 ◽  
Author(s):  
Yingna Chen ◽  
Tao Hou ◽  
Sha Meng ◽  
Shan Zhong ◽  
Jia Liu
Keyword(s):  
Keyword Spotting ◽  
Confidence Measure ◽  
Large Vocabulary ◽  
New Framework

A New SVM Kernel for Keyword Spotting Using Confidence Measures

2015 ◽  
Vol 24 (03) ◽  
pp. 1550010 ◽  
Author(s):  
Yassine Ben Ayed
Keyword(s):  
Support Vector Machines ◽  
Hidden Markov ◽  
Support Vector ◽  
Svm Classifier ◽  
Keyword Spotting ◽  
Confidence Measure ◽  
Confidence Measures ◽  
Vector Machines ◽  
Harmonic Means ◽  
Speech Recognizer

In this paper, we propose an alternative keyword spotting method relying on confidence measures and support vector machines. Confidence measures are computed from phone information provided by a Hidden Markov Model based speech recognizer. We use three kinds of techniques, i.e., arithmetic, geometric and harmonic means to compute a confidence measure for each word. The acceptance/rejection decision of a word is based on the confidence vector processed by the SVM classifier for which we propose a new Beta kernel. The performance of the proposed SVM classifier is compared with spotting methods based on some confidence means. Experimental results presented in this paper show that the proposed SVM classifier method improves the performances of the keyword spotting system.

scholarly journals A Russian Keyword Spotting System Based on Large Vocabulary Continuous Speech Recognition and Linguistic Knowledge

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Valentin Smirnov ◽  
Dmitry Ignatov ◽  
Michael Gusev ◽  
Mais Farkhadov ◽  
Natalia Rumyantseva ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Real Life ◽  
Training Data ◽  
Linguistic Knowledge ◽  
Keyword Spotting ◽  
Continuous Speech ◽  
Continuous Speech Recognition ◽  
Large Vocabulary ◽  
Effective Combination ◽  
Industrial Use

The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use.

A fast algorithm for large vocabulary keyword spotting application

1994 ◽  
Vol 2 (3) ◽  
pp. 449-452 ◽  
Author(s):  
Eng-Fong Huang ◽  
Hsiao-Chuan Wang ◽  
F.K. Soong
Keyword(s):  
Fast Algorithm ◽  
Keyword Spotting ◽  
Large Vocabulary
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