P. Isabelle, Marc Dymetman, George F. Foster, Jean-Marc Jutras, E. Macklovitch, F. Perrault, Xiaobo Ren, Michel Simard
We argue that the concept of translation analysis provides a suitable foundation for a new generation of translation support tools. We show that pre-existing translations can be analyzed into a structured translation memory and describe our TransSearch bilingual concordancing system, which allows translators to harness such a memory. We claim that translation analyzers can help detect translation errors in draft translations and we present the results of an experiment on the detection of deceptive cognates conducted as part of our TransCheck project. Finally, we claim that translation analysis can facilitate the speech-to-text transcription of dictated translations and introduce our new TransTalk project.
{"title":"Translation Analysis and Translation Automation","authors":"P. Isabelle, Marc Dymetman, George F. Foster, Jean-Marc Jutras, E. Macklovitch, F. Perrault, Xiaobo Ren, Michel Simard","doi":"10.1145/962416","DOIUrl":"https://doi.org/10.1145/962416","url":null,"abstract":"We argue that the concept of translation analysis provides a suitable foundation for a new generation of translation support tools. We show that pre-existing translations can be analyzed into a structured translation memory and describe our TransSearch bilingual concordancing system, which allows translators to harness such a memory. We claim that translation analyzers can help detect translation errors in draft translations and we present the results of an experiment on the detection of deceptive cognates conducted as part of our TransCheck project. Finally, we claim that translation analysis can facilitate the speech-to-text transcription of dictated translations and introduce our new TransTalk project.","PeriodicalId":345684,"journal":{"name":"Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114545638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In a recent paper, Gale and Church describe an inexpensive method for aligning bitext, based exclusively on sentence lengths [3]. While this method produces surprisingly good results (a success rate around 96%), even better results are required to perform such tasks as the computer-assisted revision of translations. In this paper, we examine some of the weaknesses of Gale and Church's program, and explain how just a small amount of linguistic knowledge would help to overcome these weaknesses. We discuss how cognates provide for a cheap and reasonably reliable source of linguistic knowledge. To illustrate this, we describe a modification to the program in which the criterion is cognates rather than sentence lengths. Finally, we show how better and more efficient results may be obtained by combining the two criteria length and "cogneteness". Our method can be generalized to accommodate other sources of linguistic knowledge, and experimentation shows that it produces better results than alignments based on length alone, at a minimal cost.
{"title":"Using cognates to align sentences in bilingual corpora","authors":"Michel Simard, George F. Foster, P. Isabelle","doi":"10.1145/962411","DOIUrl":"https://doi.org/10.1145/962411","url":null,"abstract":"In a recent paper, Gale and Church describe an inexpensive method for aligning bitext, based exclusively on sentence lengths [3]. While this method produces surprisingly good results (a success rate around 96%), even better results are required to perform such tasks as the computer-assisted revision of translations. In this paper, we examine some of the weaknesses of Gale and Church's program, and explain how just a small amount of linguistic knowledge would help to overcome these weaknesses. We discuss how cognates provide for a cheap and reasonably reliable source of linguistic knowledge. To illustrate this, we describe a modification to the program in which the criterion is cognates rather than sentence lengths. Finally, we show how better and more efficient results may be obtained by combining the two criteria length and \"cogneteness\". Our method can be generalized to accommodate other sources of linguistic knowledge, and experimentation shows that it produces better results than alignments based on length alone, at a minimal cost.","PeriodicalId":345684,"journal":{"name":"Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115822962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Brown, J. Cocke, S. D. Pietra, V. D. Pietra, F. Jelinek, R. Mercer, P. Roossin
In this paper we will outline an approach to automatic translation that utilizes techniques of statistical information extraction from large data bases. These self-organizing techniques have proven successful in the field of automatic speech recognition [1,2,3]. Statistical approaches have also been used recently in lexicography [4] and natural language processing [3,5,6]. The idea of automatic translation by statistical (information theoretic) methods was proposed many years ago by Warren Weaver [7].
{"title":"A statistical approach to French/English translation","authors":"P. Brown, J. Cocke, S. D. Pietra, V. D. Pietra, F. Jelinek, R. Mercer, P. Roossin","doi":"10.5555/3170668.3170681","DOIUrl":"https://doi.org/10.5555/3170668.3170681","url":null,"abstract":"In this paper we will outline an approach to automatic translation that utilizes techniques of statistical information extraction from large data bases. These self-organizing techniques have proven successful in the field of automatic speech recognition [1,2,3]. Statistical approaches have also been used recently in lexicography [4] and natural language processing [3,5,6]. The idea of automatic translation by statistical (information theoretic) methods was proposed many years ago by Warren Weaver [7].","PeriodicalId":345684,"journal":{"name":"Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125330585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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