ESTABLISHING A METHODOLOGY FOR BENCHMARKING SPEECH SYNTHESIS FOR COMPUTER-ASSISTED LANGUAGE LEARNING (CALL) - Zöe Handley; Marie-Josée Hamel (Language Learning and Technology)
Despite the new possibilities that speech synthesis brings about, few Computer-Assisted Language Learning (CALL) applications integrating speech synthesis have found their way onto the market. One potential reason is that the suitability and benefits of the use of speech synthesis in CALL have not been proven. One way to do this is through evaluation. Yet, very few formal evaluations of speech synthesis for CALL purposes have been conducted. One possible reason for the neglect of evaluation in this context is the fact that it is expensive in terms of time and resources. An important concern given that there are several levels of evaluation from which such applications would benefit. Benchmarking, the comparison of the score obtained by a system with that obtained by one which is known, to guarantee user satisfaction in a standard task or set of tasks, is introduced as a potential solution to this problem. In this article, we report on our progress towards the development of one of these benchmarks, namely a benchmark for determining the adequacy of speech synthesis systems for use in CALL. We do so by presenting the results of a case study which aimed to identify the criteria which determine the adequacy of the output of speech synthesis systems for use in its various roles in CALL with a view to the selection of benchmark tests which will address these criteria. These roles (reading machine, pronunciation model, and conversational partner) are also discussed here. An agenda for further research and evaluation is proposed in the conclusion.