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In this study, a new keyword spotting system (KWS) that utilizes phone confusion networks (PCNs) is presented. The new system exploits the compactness and accuracy of phone confusion networks to deliver fast and accurate results. Special design considerations are provided within the new algorithm to account for phone
In this paper we develop an approach to automatic, data-driven generation of pronunciation dictionaries for keyword spotting(KWS) systems. In practical applications, KWS tasks often have to deal with keywords whose pronunciations can not be found in the dictionary. To solve this problem, we study how to derive
Being able to search for words or phrases in historic handwritten documents is of paramount importance when preserving cultural heritage. Storing scanned pages of written text can save the information from degradation, but it does not make the textual information readily available. Automatic keyword spotting systems
One of the most important steps in a keyword spotting (KWS) system is a post-processing procedure to compute a confidence measure (CM) for each hypothesized keyword. The CM is commonly estimated by likelihood-based acoustic scores. However durations of the detected keyword, which include useful information, has not
the userpsilas acoustic signal from a singing voice and retrieves the music information using both lyrics and melody information. The lyrics recognition module uses a keyword spotting system based on text-content of the lyrics by an HMM comparison engine. The melody recognition module extracts pitch and MFCC features
General purpose computation based on GPU is a hot topic for research in recent years. The paper presents the parallel implementation of Viterbi algorithm on GPU based on features of GPU and characteristics of Viterbi algorithm in keyword spotting system. The results of examination by using NVIDIA 9600 GT GPU show that
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