Speech synthesis or text-to-speech (TTS) systems are currently available for a number of the world's major languages, but for thousands of other, unsupported, languages no such technology is available. While awaiting the development of such technology, we propose using an existing TTS system for a major language (the base language, BL) to "fake" TTS for an unsupported language (the target language, TL). This paper describes the factors which determine the choice of a suitable BL for a given TL, and describe an experiment with a fake Somali TTS system evaluated in the real-life situation of a doctor–patient dialogue. 28 Somali participants were asked to judge the comprehensibility of 25 short Somali sentences recorded with a German TTS system. Results suggest that "faking it" provides reasonable stop-gap TTS for unsupported languages.

While spoken language translation remains a research goal, a crude form of it is widely available commercially for Japanese–English as a pipeline concatenation of speech-to-text recognition (SR), text-to-text translation (MT) and text-to-speech synthesis (SS). This paper proposes and illustrates an evaluation methodology for this noisy channel which tries to quantify the relative amount of degradation in translation quality due to each of the contributing modules. A small pilot experiment involving word-accuracy rate for the SR, and a fidelity evaluation for the MT and SS modules is proposed in which subjects are asked to paraphrase translated and/or synthesised sentences from a tourist’s phrasebook. Results show (as expected) that MT is the “noisiest” channel, with SS contributing least noise. The concatenation of the three channels is worse than could be predicted from the performance of each as individual tasks.

This paper describes a number of “toy” MT systems written in Prolog, designed as programming exercises and illustrations of various approaches to MT. The systems include a dumb word-for-word system, DCG-based “transfer” system, an interlingua-based system with an LFG-like interface structure, a first-generation-like Russian-English system, an interactive system, and an implementation based on early example-based MT.

This paper looks at EBMT from the perspective of the Case-based Reasoning (CBR) paradigm. We attempt to describe the task of machine translation (MT) seen as a potential application of CBR, and attempt to describe MT in standard CBR terms. The aim is to see if other applications of CBR can suggest better ways to approach EBMT.

This paper considers the role of translation software, especially Machine Translation (MT), in curricula for students of computational linguistics, for trainee translators and for language learners. These three sets of students have differing needs and interests, although there is some overlap between them. A brief historical view of MT in the classroom is given, including comments on the author’s 25 years of experience in the field. This is followed by discussion and examples of strategies for teaching about MT and related aspects of Language Engineering and Information Technology for the three types of student.

This paper discusses an informal methodology for evaluating Machine Translation software documentation with reference to a case study, in which a number of currently available MT packages are evaluated. Different types of documentation style are discussed, as well as different user profiles. It is found that documentation is often inadequate in identifying the level of linguistic background and knowledge necessary to use translation software, and in explaining technical (linguistic) terms needed to use the software effectively. In particular, the level of knowledge and training needed to use the software is often incompatible with the user profile implied by the documentation. Also, guidance on how to perform more complex tasks, which may be especially idiosyncratic, is often inadequate or missing altogether.

Language Engineering (LE) products and resources for the world’s “major” languages are steadily increasing, but there remains a major gap as regards less widely-used languages. This paper considers the current situation regarding LE resources for some of the languages in question, and some proposals for rectifying this situation are made, including techniques based on adapting existing resources and “knowledge extraction” techniques from machine-readable corpora.

This paper aims to survey the current state of research, development and use of Machine Translation (MT). Under ‘research’ the role of linguistics is discussed, and contrasted with research in ‘analogy- based’ MT. The range of languages covered by MT systems is discussed, and the lack of development for minority languages noted. The new research area of spoken language translation (SLT) is reviewed, with some major differences between SLT and text MT described. Under ‘use and users’ we discuss tools for users: Translation Memory, bilingual concordances and software to help checking for mistranslations. The use of MT on the World Wide Web is also discussed, regarding pre- and post-editing, the impact of ‘controlled language’ is reviewed, and finally a proposal is made that MT users can revise the input text in the light of errors that the system makes, thus ‘post-editing the source text’.