The aim of the thesis is to find out whether providing feedback to Arabic language learners will help them improve their pronunciation, particularly of words involving sounds that are not distinguished in their native languages. In addition, it aims to find out, if possible, what type of feedback will be most helpful. In order to achieve this aim, we developed a computational tool with a number of component sub tools. These tools involve the implementation of several substantial pieces of software. The first task was to ensure the system we were building could distinguish between the more challenging sounds when they were produced by a native speaker, since without that it will not be possible to classify learners’ attempts at these sounds. To this end, a number of experiments were carried out with the hidden Markov model toolkit (the HTK), a well known speech recognition toolkit, in order to ensure that it can distinguish between the confusable sounds, i.e. the ones that people have difficulty with. The developed computational tool analyses the differences between the user’s pronunciation and that of a native speaker by using grammar of minimal pairs, where each utterance is treated as coming from a family of similar words. This provides the ability to categorise learners’ errors - if someone is trying to say cat and the recogniser thinks they have said cad then it is likely that they are voicing the final consonant when it should be unvoiced. Extensive testing shows that the system can reliably distinguish such minimal pairs when they are produced by a native speaker, and that this approach does provide effective diagnostic information about errors. The tool provides feedback in three different sub-tools: as an animation of the vocal tract, as a synthesised version of the target utterance, and as a set of written instructions. The tool was evaluated by placing it in a classroom setting and asking 50 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. The results of this group showed that their pronunciation does improve over the course of the session, though it was not possible to determine whether the improvement is sustained over an extended period. The evaluation was done from three points of view: quantitative analysis, qualitative analysis, and using a questionnaire. Firstly, the quantitative analysis gives raw numbers telling whether a learner had improved their pronunciation or not. Secondly, the qualitative analysis shows a behaviour pattern of what a learner did and how they used the tool. Thirdly, the questionnaire gives feedback from learners and their comments about the tool. We found that providing feedback does appear to help Arabic language learners, but we did not have enough data to see which form of feedback is most helpful. However, we provided an informative analysis of behaviour patterns to see how Arabic students used the tool and interacted with it, which could be useful for more data analysis.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:654799 |
| Date | January 2015 |
| Creators | Alsabaan, Majed Soliman K. |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.research.manchester.ac.uk/portal/en/theses/pronunciation-support-for-arabic-learners(3db28816-90ed-4e8b-b64c-4bbd35f98be7).html |
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