Abstract
This paper reports the development of Urdu keyword spotting system (KWS). The approach in the development of KWS is based on filler models to account for non-keywords speech intervals. An impact of using different training datasets to develop filler models has been explored. In addition, a phoneme recognizer (PR) based on all phone model automatic speech recognition system (ASR) has been developed on keywords. Training and decoding parameters of KWS system have been tweaked to get the optimum performance. In the end, KWS and PR systems are integrated and string matching algorithm has been used to improve the performance of Urdu keyword spotter system. The overall system accuracy is 94.59% on the data set used.
Sarmad Hussain, Khawer Rehman, Saad Irtza. (2014) Urdu Keyword Spotting System using HMM, Conference on Language and Technology 2014.
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Publisher
Center for Language Engineering
Country
Pakistan
City
Karachi
From
13-11-2014
To
15-11-2014