TY - GEN
T1 - Estimation of speaking style in speech corpora focusing on speech transcriptions
AU - Shen, Raymond
AU - Kikuchi, Hideaki
PY - 2014
Y1 - 2014
N2 - Recent developments in computer technology have allowed the construction and widespread application of large-scale speech corpora. To foster ease of data retrieval for people interested in utilising these speech corpora, we attempt to characterise speaking style across some of them. In this paper, we first introduce the 3 scales of speaking style proposed by Eskenazi in 1993. We then use morphological features extracted from speech transcriptions that have proven effective in style discrimination and author identification in the field of natural language processing to construct an estimation model of speaking style. More specifically, we randomly choose transcriptions from various speech corpora as text stimuli with which to conduct a rating experiment on speaking style perception; then, using the features extracted from those stimuli and the rating results, we construct an estimation model of speaking style by a multi-regression analysis. After the cross validation (leave-1-out), the results show that among the 3 scales of speaking style, the ratings of 2 scales can be estimated with high accuracies, which prove the effectiveness of our method in the estimation of speaking style.
AB - Recent developments in computer technology have allowed the construction and widespread application of large-scale speech corpora. To foster ease of data retrieval for people interested in utilising these speech corpora, we attempt to characterise speaking style across some of them. In this paper, we first introduce the 3 scales of speaking style proposed by Eskenazi in 1993. We then use morphological features extracted from speech transcriptions that have proven effective in style discrimination and author identification in the field of natural language processing to construct an estimation model of speaking style. More specifically, we randomly choose transcriptions from various speech corpora as text stimuli with which to conduct a rating experiment on speaking style perception; then, using the features extracted from those stimuli and the rating results, we construct an estimation model of speaking style by a multi-regression analysis. After the cross validation (leave-1-out), the results show that among the 3 scales of speaking style, the ratings of 2 scales can be estimated with high accuracies, which prove the effectiveness of our method in the estimation of speaking style.
KW - Estimation
KW - Speaking style
KW - Transcriptions
UR - http://www.scopus.com/inward/record.url?scp=85037124545&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85037124545&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85037124545
T3 - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
SP - 2747
EP - 2752
BT - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
A2 - Calzolari, Nicoletta
A2 - Choukri, Khalid
A2 - Goggi, Sara
A2 - Declerck, Thierry
A2 - Mariani, Joseph
A2 - Maegaard, Bente
A2 - Moreno, Asuncion
A2 - Odijk, Jan
A2 - Mazo, Helene
A2 - Piperidis, Stelios
A2 - Loftsson, Hrafn
PB - European Language Resources Association (ELRA)
T2 - 9th International Conference on Language Resources and Evaluation, LREC 2014
Y2 - 26 May 2014 through 31 May 2014
ER -