\ , I \ I I The problem Of discriminating keyword and non-keyword speech which is important in wordspotting applications is addressed here. We have shown that garbage models cannot reduce both rejection and false alarm rates simultaneously. Thus, the following relation becomes apparent from the above inequalities O'In I ) > " ( o ' l l P ) . P(08 I R P ) > p(oP I R 1 ) (4) TO achieve this we ha...

Abstract—Keyword Search is known as a user-friendly alternative for structured languages to retrieve information from graph-structured data. Efficient retrieving of relevant answers to a keyword query and effective ranking of these answers according to their relevance are two main challenges in the keyword search over graph-structured data. In this paper, a novel scoring function is proposed, w...

For robust speech translation, we propose a new language translation method in which speech recognition results are mapped to example sentences using keywords. In this method, the keyword clustering is used to cope with recognition errors and the wide variety of words that do not appear in the training corpus. Initial classes defined using only thesaurus are redefined by using the dependency be...

Considering the magneto-hydrodynamic equations in a non-relativistic multi uid framework, we study the behavior of small amplitude perturbations in cold quark matter. Magneto-hydrodynamic equations, along with a suitable equation of state for the cold quark matter, are expanded using the reductive perturbation method. It is shown that in small amplitude approximation, such a medium should be co...

Conventional search engines nd Web pages by using keyword matching. Two disadvantages for keyword matching are: (i) the order of keywords is ignored; and (ii) the approximate queries submitted by users are beyond the method of keyword matching can handle. Using keyword matching for Web page search is not satisfactory. This paper proposes a Web search system, named ApproxSeek, to facilitate Web ...

We present a novel method for translating keyword queries over relational databases into SQL queries with the same intended semantic meaning. In contrast to the majority of the existing keyword-based techniques, our approach does not require any a-priori knowledge of the data instance. It follows a probabilistic approach based on a Hidden Markov Model for computing the top-K best mappings of th...

Today an efficient information search is very important to extract and analyze user requirements in vast amount of web information. Due to this reason, this paper proposes the log based keyword extraction method which finds the associated keywords in a certain domain. Also, this paper proposes the spread based clustering method as clustering the keywords with high association among the keyword-...

Keyword search in relational databases has been widely studied in recent years because it does not require users neither to master a certain structured query language nor to know the complex underlying database schemas. Most of existing methods focus on answering snapshot keyword queries in static databases. In practice, however, databases are updated frequently, and users may have long-term in...