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It's Been Said Before

By Orin Hargraves

It's Been Said Before "examines why certain phrases become clichés and why they should be avoided -- or why they still have life left in them."

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By J. C. Wells

How do you pronounce biopic, synod, and Breughel? - and why? Do our cake and archaic sound the same? Where does the stress go in stalagmite? What's odd about the word epergne? As a finale, the author writes a letter to his 16-year-old self.

Academic Paper

Title: Is Text-to-Speech Synthesis Ready for Use in Computer-Assisted Language Learning?
Paper URL:
Author: Zoe Louise Handley
Email: click here TO access email
Institution: University of Oxford
Linguistic Field: Applied Linguistics; Computational Linguistics
Abstract: Text-to-speech (TTS) synthesis, the generation of speech from text input, offers another means of providing spoken language input to learners in Computer-Assisted Language Learning (CALL) environments. Indeed, many potential benefits (ease of creation and editing of speech models, generation of speech models and feedback on demand, etc.) and uses (talking dictionaries, talking texts, dictation, pronunciation training, dialogue partner, etc.) of TTS synthesis in CALL have been put forward. Yet, the use of TTS synthesis in CALL is not widely accepted and only a few applications have found their way onto the market. One potential reason for this is that TTS synthesis has not been adequately evaluated for this purpose. Previous evaluations of TTS synthesis for use in CALL, have only addressed the comprehensibility of TTS synthesis. Yet, CALL places demands on the comprehensibility, naturalness, accuracy, register and expressiveness of the output of TTS synthesis. In this paper, the aforementioned aspects of the quality of the output of four state-of-the-art French TTS synthesis systems are evaluated with respect to their use in the three different roles that TTS synthesis systems may assume within CALL applications, namely: (1) reading machine, (2) pronunciation model and (3) conversational partner [Handley, Z., Hamel, M.-J., 2005. Establishing a methodology for benchmarking speech synthesis for computer-assisted language learning (CALL). Language Learning and Technology Journal 9(3), 99–119. Retrieved from:]. The results of this evaluation suggest that the best TTS synthesis systems are ready for use in applications in which they ‘add value’ to CALL, i.e. exploit the unique capacity of TTS synthesis to generate speech models on demand. An example of such an application is a dialogue partner. In order to fully meet the requirements of CALL, further attention needs to be paid to accuracy and naturalness, in particular at the prosodic level, and expressiveness.
Type: Individual Paper
Status: In Progress
Publication Info: Speech Communication
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