5 resultados para Indian sign language
em Cochin University of Science
Resumo:
This paper presents the design and development of a frame based approach for speech to sign language machine translation system in the domain of railways and banking. This work aims to utilize the capability of Artificial intelligence for the improvement of physically challenged, deaf-mute people. Our work concentrates on the sign language used by the deaf community of Indian subcontinent which is called Indian Sign Language (ISL). Input to the system is the clerk’s speech and the output of this system is a 3D virtual human character playing the signs for the uttered phrases. The system builds up 3D animation from pre-recorded motion capture data. Our work proposes to build a Malayalam to ISL
Resumo:
This work is aimed at building an adaptable frame-based system for processing Dravidian languages. There are about 17 languages in this family and they are spoken by the people of South India.Karaka relations are one of the most important features of Indian languages. They are the semabtuco-syntactic relations between verbs and other related constituents in a sentence. The karaka relations and surface case endings are analyzed for meaning extraction. This approach is comparable with the borad class of case based grammars.The efficiency of this approach is put into test in two applications. One is machine translation and the other is a natural language interface (NLI) for information retrieval from databases. The system mainly consists of a morphological analyzer, local word grouper, a parser for the source language and a sentence generator for the target language. This work make contributios like, it gives an elegant account of the relation between vibhakthi and karaka roles in Dravidian languages. This mapping is elegant and compact. The same basic thing also explains simple and complex sentence in these languages. This suggests that the solution is not just ad hoc but has a deeper underlying unity. This methodology could be extended to other free word order languages. Since the frame designed for meaning representation is general, they are adaptable to other languages coming in this group and to other applications.
Resumo:
We have studied sea surface temperature (SST) anomalies over the Indian and Pacific Oceans (domain 25 °S to 25°N and 40 °E to 160 °W) during the three seasons following the Indian summer monsoon for wet monsoons and also for dry monsoons accompanied or not by El Ni˜no. A dry monsoon is followed by positive SST anomalies in the longitude belt 40 to 120 °E, negative anomalies in 120 to 160 °E and again positive anomalies east of 160 °E. In dry monsoons accompanied by El Ni˜no the anomalies have the same sign, but are much stronger. Wet monsoons have weak anomalies of opposite sign in all three of the longitude belts. Thus El Ni˜no and a dry monsoon have the same types of association with the Indian and Pacific Ocean SSTs. In the sector 40 to 120 °E SST anomalies first appear over the western part of the Indian Ocean (June to September) followed by the same sign of anomalies over its eastern part and China Sea (October to March). By March after a dry monsoon or El Ni˜no the Indian Ocean between 10 °N and 10 °S has a spatially large warm SST anomaly. Anomalies in deep convection tend to follow the SST anomalies, with warm SST anomalies producing positive convection anomalies around the seasonal location of the intertropical convergence zone
Resumo:
Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu
Resumo:
A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.