Comparison between random and daily speech database in the speech visualization

This paper presents a new technique using animated texts as the speech features' visualization medium for checking and detecting language learners' pronunciation. The proposed visualization tool will transform learners' speech features such as pitch, tempo or rhythm into animated texts form, and the mispronounce parts can be located by comparing them with the correct sample. In our previous experiments, Japanese language learners gave positive feedback on the animated texts designs as their speech visualization tool. By practicing this tool, learners found that the mispronounce parts in their speech can be detected and confirmed easily. However, in order to have more practical feedback and response from the learners, besides using the plain speech data set, which only express random speech contents, the daily conversation speech data set is proposed as the data sample. In this paper, the comparison between both database samples for determining the proposed visualization tool's approachability was observed. Evaluation experiments results showed that participants gave positive responses to the animated texts visualization tool and were able to understand speech features in the visualized texts form better by using the daily conversation as the speech sample.