TY - GEN
T1 - Animated texts application in visualizing speech features for Foreign language learning
AU - Samsudin, Nur Syafikah Binti
AU - Mano, Kazunori
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - Pronunciation training aid using media tools such as mobile apps and online web-based system are widely used nowadays. These tools often provide audio-based sample and phonetic style texts that can be used to support the learners train their pronunciation without language teachers. However, the learners still have the difficulty in the learning process, because they found it is hard to detect and locate the mispronounced parts in their own speech while practicing. In this paper, we present a method that enables to visualize speech detailed features such as pitch, intensity and duration into the text forms. The medium to portray those speech features is the animated texts which enable to express the speech features in the attributes of text features such as text size, color, position or motion. By viewing the speech features in the rich text forms like the animated texts, the learners can easily spot their mispronounced parts and correct them. Here, we examined how the actual analyzed speech data can be mapped into the animated texts' features and the effectiveness of using the proposed visualization system in portraying speech pitch, intensity and duration features. The evaluation experiments were surveyed by forty non-native Japanese learners who are Malaysian novice level learners. The experiment subjects appeared to agree with the animated texts as the representative for speech visualization and the daily conversation based speech data appeared to be an easy approach for the novice level.
AB - Pronunciation training aid using media tools such as mobile apps and online web-based system are widely used nowadays. These tools often provide audio-based sample and phonetic style texts that can be used to support the learners train their pronunciation without language teachers. However, the learners still have the difficulty in the learning process, because they found it is hard to detect and locate the mispronounced parts in their own speech while practicing. In this paper, we present a method that enables to visualize speech detailed features such as pitch, intensity and duration into the text forms. The medium to portray those speech features is the animated texts which enable to express the speech features in the attributes of text features such as text size, color, position or motion. By viewing the speech features in the rich text forms like the animated texts, the learners can easily spot their mispronounced parts and correct them. Here, we examined how the actual analyzed speech data can be mapped into the animated texts' features and the effectiveness of using the proposed visualization system in portraying speech pitch, intensity and duration features. The evaluation experiments were surveyed by forty non-native Japanese learners who are Malaysian novice level learners. The experiment subjects appeared to agree with the animated texts as the representative for speech visualization and the daily conversation based speech data appeared to be an easy approach for the novice level.
KW - animated texts
KW - language learning
KW - speech paralinguistic
KW - speech prosodic
KW - speech visualization
UR - http://www.scopus.com/inward/record.url?scp=85044232045&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044232045&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2017.8228146
DO - 10.1109/TENCON.2017.8228146
M3 - Conference contribution
AN - SCOPUS:85044232045
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
SP - 1778
EP - 1783
BT - TENCON 2017 - 2017 IEEE Region 10 Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Region 10 Conference, TENCON 2017
Y2 - 5 November 2017 through 8 November 2017
ER -