Many different languages are spoken in India, each language being the mother tongue of tens of millions of people. While the languages and scripts are distinct from each other, the grammar and the alphabet are similar...Many different languages are spoken in India, each language being the mother tongue of tens of millions of people. While the languages and scripts are distinct from each other, the grammar and the alphabet are similar to a large extent. One common feature is that all the Indian languages are phonetic in nature. In this paper we describe the development of a translit- eration scheme Om which exploits this phonetic nature of the alphabet. Om uses ASCII characters to represent Indian language alphabets, and thus can be read directly in English, by a large number of users who cannot read script in other Indian languages than their mother tongue. It is also useful in computer applications where local language tools such as email and chat are not yet available. Another significant contribution presented in this paper is the development of a text editor for Indian languages that integrates the Om input for many Indian languages into a word processor such as Microsoft WinWord?. The text editor is also developed on Java? platform that can run on Unix machines as well. We propose this transliteration scheme as a possible standard for Indian language transliteration and keyboard entry.展开更多
On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into sc...On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into scoring student's translation on-line.Based on the theory of translation equivalence,an algorithm called "conceptual similarity matching" was developed.YanFa can assess students' translation on-line timely,generate test papers automatically,offer standard versions of translation,and the scores of each sentence to students.The evaluation proves that YanFa is practical compared with the scores given by experts.展开更多
The present paper describes the use of online free language resources for translating and expanding queries in CLIR （cross-language information retrieval）. In a previous study, we proposed method queries that were t...The present paper describes the use of online free language resources for translating and expanding queries in CLIR （cross-language information retrieval）. In a previous study, we proposed method queries that were translated by two machine translation systems on the Language Gridem. The queries were then expanded using an online dictionary to translate compound words or word phrases. A concept base was used to compare back translation words with the original query in order to delete mistranslated words. In order to evaluate the proposed method, we constructed a CLIR system and used the science documents of the NTCIR1 dataset. The proposed method achieved high precision. However~ proper nouns （names of people and places） appear infrequently in science documents. In information retrieval, proper nouns present unique problems. Since proper nouns are usually unknown words, they are difficult to find in monolingual dictionaries, not to mention bilingual dictionaries. Furthermore, the initial query of the user is not always the best description of the desired information. In order to solve this problem, and to create a better query representation, query expansion is often proposed as a solution. Wikipedia was used to translate compound words or word phrases. It was also used to expand queries together with a concept base. The NTCIRI and NTCIR 6 datasets were used to evaluate the proposed method. In the proposed method, the CLIR system was implemented with a high rate of precision. The proposed syst had a higher ranking than the NTCIRI and NTCIR6 participation systems.展开更多
文摘Many different languages are spoken in India, each language being the mother tongue of tens of millions of people. While the languages and scripts are distinct from each other, the grammar and the alphabet are similar to a large extent. One common feature is that all the Indian languages are phonetic in nature. In this paper we describe the development of a translit- eration scheme Om which exploits this phonetic nature of the alphabet. Om uses ASCII characters to represent Indian language alphabets, and thus can be read directly in English, by a large number of users who cannot read script in other Indian languages than their mother tongue. It is also useful in computer applications where local language tools such as email and chat are not yet available. Another significant contribution presented in this paper is the development of a text editor for Indian languages that integrates the Om input for many Indian languages into a word processor such as Microsoft WinWord?. The text editor is also developed on Java? platform that can run on Unix machines as well. We propose this transliteration scheme as a possible standard for Indian language transliteration and keyboard entry.
基金The National Natural Science Foundation ofChina(No.60496326)
文摘On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into scoring student's translation on-line.Based on the theory of translation equivalence,an algorithm called "conceptual similarity matching" was developed.YanFa can assess students' translation on-line timely,generate test papers automatically,offer standard versions of translation,and the scores of each sentence to students.The evaluation proves that YanFa is practical compared with the scores given by experts.
文摘The present paper describes the use of online free language resources for translating and expanding queries in CLIR （cross-language information retrieval）. In a previous study, we proposed method queries that were translated by two machine translation systems on the Language Gridem. The queries were then expanded using an online dictionary to translate compound words or word phrases. A concept base was used to compare back translation words with the original query in order to delete mistranslated words. In order to evaluate the proposed method, we constructed a CLIR system and used the science documents of the NTCIR1 dataset. The proposed method achieved high precision. However~ proper nouns （names of people and places） appear infrequently in science documents. In information retrieval, proper nouns present unique problems. Since proper nouns are usually unknown words, they are difficult to find in monolingual dictionaries, not to mention bilingual dictionaries. Furthermore, the initial query of the user is not always the best description of the desired information. In order to solve this problem, and to create a better query representation, query expansion is often proposed as a solution. Wikipedia was used to translate compound words or word phrases. It was also used to expand queries together with a concept base. The NTCIRI and NTCIR 6 datasets were used to evaluate the proposed method. In the proposed method, the CLIR system was implemented with a high rate of precision. The proposed syst had a higher ranking than the NTCIRI and NTCIR6 participation systems.
