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In keyword spotting applications, language modeling directly affects the system performance, as well as the acoustical modeling. This study focuses on the effects of different language models on the keyword spotting performance on Turkish voice recordings. Three different systems, one of which is proposed by us, that
Keyword-based search is one of the most important technologies of text search. But with the development of World Wide Web, it is not enough only relying on matching the form of keywords. This paper introduced a semantic parsing model constructed above a symbolic system of concepts for understanding natural language
The session initiation protocol (SIP) is widely used as the signaling protocol for various services in the ubiquitous environment of the home network. SIP is a text-based protocol with characteristics of unordered and verbose headers, variable-size message, case-insensitive keyword etc., which imposes challenges for
proposed a formalized model of the text semantic similarity and similarity algorithm based on the case grammar. The semantic meanings of a sentence stem decide the similarity of a sentence. To the similarity sentence, a vector is used for the decorating case to get similarity algorithm. In this way, it avoided the keyword
word segmentation and pas tagging, language modeling and term translation, text clustering, text categorization, text summarization, keywords identification in a single document and duplication detection. The application can invoke any module of LJParser in Windows and Linux using any language including C, C# and Java
domain special ontology, grammatical knowledge of text could be acquired easily, and the latter is more determinate than the former. In the area of Information Retrieval, it is not enough to search information only based on keywords. Under this situation should we consider some web application can employ grammatical
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