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ERIC Number: ED565137
Record Type: Non-Journal
Publication Date: 2014-Aug
Pages: 6
Abstractor: As Provided
Reference Count: 8
Diagnostic CALL Tool for Arabic Learners
Alsabaan, Majed; Ramsay, Allan, Paper presented at the 2014 EUROCALL Conference (Groningen, The Netherlands, Aug 20-23, 2014)
Our proposed work is aimed at teaching non-native Arabic speakers how to improve their pronunciation. This paper reports on a diagnostic tool for helping non-native speakers of Arabic improve their pronunciation, particularly of words involving sounds that are not distinguished in their native languages. The tool involves the implementation of several substantial pieces of software. The first task is to ensure the system we are building can distinguish between the more challenging sounds when they are produced by a native speaker, since without that, it will not be possible to classify learners' attempts at these sounds. To this end, we carried out a number of experiments with the well-known speech recognition Hidden Markov Model Toolkit (HTK), in order to ensure that it can distinguish between confusable sounds, such as the ones that people have difficulty with. Our diagnostic tool provides feedback in three different forms: as an animation of the vocal tract, as a synthesised version of the target utterance, and as a set of written instructions. We have evaluated the tool by placing it in a classroom setting, asking 40 Arabic students to use the different versions of the tool. Each student had a thirty minute session with the tool, working their way through a set of pronunciation exercises at their own pace. Preliminary results from this pilot group show that their pronunciation does improve over the course of the session. [For full proceedings, see ED565087.] La Grange des Noyes, 25110 Voillans, France. e-mail:; Web site:
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A