31,024 research outputs found
Improving the translation environment for professional translators
When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side.
This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project
Developing Better Non-English Materials: Understanding the Limits of Translation
Presents lessons learned from demonstration sites on the challenges of providing non-English material for patients with limited English proficiency, including misconceptions about translation and lack of effective evaluation methods. Recommends solutions
The Speech-Language Interface in the Spoken Language Translator
The Spoken Language Translator is a prototype for practically useful systems
capable of translating continuous spoken language within restricted domains.
The prototype system translates air travel (ATIS) queries from spoken English
to spoken Swedish and to French. It is constructed, with as few modifications
as possible, from existing pieces of speech and language processing software.
The speech recognizer and language understander are connected by a fairly
conventional pipelined N-best interface. This paper focuses on the ways in
which the language processor makes intelligent use of the sentence hypotheses
delivered by the recognizer. These ways include (1) producing modified
hypotheses to reflect the possible presence of repairs in the uttered word
sequence; (2) fast parsing with a version of the grammar automatically
specialized to the more frequent constructions in the training corpus; and (3)
allowing syntactic and semantic factors to interact with acoustic ones in the
choice of a meaning structure for translation, so that the acoustically
preferred hypothesis is not always selected even if it is within linguistic
coverage.Comment: 9 pages, LaTeX. Published: Proceedings of TWLT-8, December 199
Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration
Cross-language information retrieval (CLIR), where queries and documents are
in different languages, has of late become one of the major topics within the
information retrieval community. This paper proposes a Japanese/English CLIR
system, where we combine a query translation and retrieval modules. We
currently target the retrieval of technical documents, and therefore the
performance of our system is highly dependent on the quality of the translation
of technical terms. However, the technical term translation is still
problematic in that technical terms are often compound words, and thus new
terms are progressively created by combining existing base words. In addition,
Japanese often represents loanwords based on its special phonogram.
Consequently, existing dictionaries find it difficult to achieve sufficient
coverage. To counter the first problem, we produce a Japanese/English
dictionary for base words, and translate compound words on a word-by-word
basis. We also use a probabilistic method to resolve translation ambiguity. For
the second problem, we use a transliteration method, which corresponds words
unlisted in the base word dictionary to their phonetic equivalents in the
target language. We evaluate our system using a test collection for CLIR, and
show that both the compound word translation and transliteration methods
improve the system performance
Analysis of errors in the automatic translation of questions for translingual QA systems
Purpose â This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question-answer (QA) systems. The efficacy of online translators when performing as tools in QA systems is analysed using a collection of documents in the Spanish language.
Design/methodology/approach â Automatic translation is evaluated in terms of the functionality of actual translations produced by three online translators (Google Translator, Promt Translator, and Worldlingo) by means of objective and subjective evaluation measures, and the typology of errors produced was identified. For this purpose, a comparative study of the quality of the translation of factual questions of the CLEF collection of queries was carried out, from German and French to Spanish.
Findings â It was observed that the rates of error for the three systems evaluated here are greater in the translations pertaining to the language pair German-Spanish. Promt was identified as the most reliable translator of the three (on average) for the two linguistic combinations evaluated. However, for the Spanish-German pair, a good assessment of the Google online translator was obtained as well. Most errors (46.38 percent) tended to be of a lexical nature, followed by those due to a poor translation of the interrogative particle of the query (31.16 percent).
Originality/value â The evaluation methodology applied focuses above all on the finality of the translation. That is, does the resulting question serve as effective input into a translingual QA system? Thus, instead of searching for âperfectionâ, the functionality of the question and its capacity to lead one to an adequate response are appraised. The results obtained contribute to the development of
improved translingual QA systems
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