Changki Lee et al. 179 We propose a multi-strategic concept-spotting approach for robust spoken language understanding of conversational Korean in a hostile recognition environment such as in-car navigation and telebanking services. Our concept-spotting method adopts a partial semantic understanding strategy within a given specific domain since the method tries to directly extract predefined me...

Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely...

This paper explores one dimension along which word spotting and speech recognition differ: the nature of the background model. In word spotting, a relatively small number of keywords float on a sea of unknown words. In speech recognition, an occasional unknown word punctuates utterances that are otherwise completely invocabulary. Despite this difference in viewpoint, in some circumstances imple...

In this paper, we propose a web-based bilingual concordancer, DOMCAT 1 , for domain-specific computer assisted translation. Given a multi-word expression as a query, the system involves retrieving sentence pairs from a bilingual corpus, identifying translation equivalents of the query in the sentence pairs (translation spotting) and ranking the retrieved sentence pairs according to the relevanc...

Micro-expressions (MEs) are brief and involuntary facial expressions that occur when people trying to hide their true feelings or conceal emotions. Based on psychology research, MEs play an important role in understanding genuine emotions, which leads many potential applications. Therefore, ME analysis has become attractive topic for various research areas, such as psychology, law enforcement, ...

In the deployment of scene-text spotting systems on mobile platforms, lightweight models with low computation are preferable. concept, end-to-end (E2E) text is suitable for such purposes because it performs detection and recognition in a single model. However, current state-of-the-art E2E methods rely heavy feature extractors, recurrent sequence modellings, complex shape aligners to pursue accu...

A Novel Image Matching Approach for Word Spotting Muhammad Ismail Shah Word spotting has been adopted and used by various researchers as a complementary technique to Optical Character Recognition for document analysis and retrieval. The various applications of word spotting include document indexing, image retrieval and information filtering. The important factors in word spotting techniques ar...

In 1919 Castle" 2 showed the dominant English spotting pattern of the rabbit to be closely linked with the recessive Dutch spotting pattern, and in 1924 he published evidence proving that both English and Dutch are linked with Angora. In the latter year I began experiments designed to learn whether or not there exists a corresponding linkage between dominant and recessive spotting in the house ...

In this paper, we explore and evaluate the use of ranking-based objective functions for learning simultaneously a word string image encoder. We consider retrieval frameworks in which user expects list ranked according to defined relevance score. context spotting problem, score has been set edit distance from query string. experimentally demonstrate competitive performance proposed model on quer...