King Kui Sin

Terminological equivalence in legal translation: A semiotic approach

Abstract Equivalence has been a critical issue in translation, as well as in legal translation. Based on a literature review of the concept of equivalence and analysis of the features of legal discourses, the article adopts a semiotic approach to the translation of legal terms. By adapting some principal propositions in semiotics, the paper argues that total equivalence can be achieved via meta-lingual adjustment, because a sign is not born with meaning but invested with reference by a sign user. The paper also provides some linguistic strategies for realizing terminological equivalence in legal translation, such as the use of a semantic reference scheme, componential analysis, and the principle of productivity and economy.

A sociosemiotic interpretation of linguistic modality in legal settings

Abstract While a much investigated concept because of its importance in shaping human discourse, modality has still not been given an agreed understanding. Using authentic Chinese court judgments in Hong Kong, this paper aims to unravel the complexity of modality as exemplified in its usage in the legal domain. It examines formal, semantic, and functional approaches to modality, showing their weaknesses in identifying and explaining modality in legal discourse. It proposes a socio-semiotic approach as an alternative for giving us a better understanding of modality in respect of its meaning and function in our language as a sign system.

Some considerations on guidelines for bilingual alignment and terminology extraction

Despite progress in the development of computational means, human input is still critical in the production of consistent and useable aligned corpora and term banks. This is especially true for specialized corpora and term banks whose end-users are often professionals with very stringent requirements for accuracy, consistency and coverage. In the compilation of a high quality Chinese-English legal glossary for ELDoS project, we have identified a number of issues that make the role human input critical for term alignment and extraction. They include the identification of low frequency terms, paraphrastic expressions, discontinuous units, and maintaining consistent term granularity, etc. Although manual intervention can more satisfactorily address these issues, steps must also be taken to address intra- and inter-annotator inconsistency.

Court Stenography-To-Text ("STT") in Hong Kong: A Jurilinguistic Engineering Effort

Implementation of legal bilingualism in Hong Kong after 1997 has necessitated the production of voluminous and extensive court proceedings and judgments in both Chinese and English. For the Chinese records, Cantonese, a dialect of Chinese, is the home language of more than 90% of the population in Hong Kong and is thus officially used in the courts. For the court proceedings, Cantonese speech would have to be recorded, and a Cantonese Computer-Aided Transcription system has been developed. The transcription system converts stenographic codes into Chinese text, i.e. from phonetic to orthographic representation of the language. The main challenge lies in the resolution of the severe ambiguity resulting from homocode problems in the conversion process. Cantonese Chinese is typified by problematic homonymy, which presents serious challenges. The N-gram statistical model is employed to estimate the most probable character string of the input transcription codes. Domain-specific corpora have been compiled to support the statistical computation. To improve accuracy, scalable techniques such as domain-specific transcription and special encoding are used. Put together, these techniques deliver 96% transcription accuracy.

Jurilinguistic engineering in Cantonese Chinese: an N -gram-based speech to text transcription system

A Cantonese Chinese transcription system to automatically convert stenograph code to Chinese characters is reported. The major challenge in developing such a system is the critical homocode problem because of homonymy. The statistical N-gram model is used to compute the best combination of characters. Supplemented with a 0.85 million character corpus of domain-specific training data and enhancement measures, the bigram and trigram implementations achieve 95% and 96% accuracy respectively, as compared with 78% accuracy in the baseline model. The system performance is comparable with other advanced Chinese Speech-to-Text input applications under development. The system meets an urgent need of the Judiciary of post-1997 Hong Kong.