Analysis of Sad Speech and Neutral-Sad Speech Conversion

Ya Hui Hou; Xiao Yue Ma; Rui Yuan; Zhong Zhe Xiao

doi:10.4028/www.scientific.net/AMM.713-715.1605

Paper Titles

An Improved Mean Shift Segmentation Method of High-Resolution Remote Sensing Image Based on LBP and Canny Features
p.1589

Analysis and Comparison of Image Enhancement Methods
p.1593

Analysis of Ceramic Pattern Primitives Transform Operation
p.1597

Analysis of KATL Operation Simulated by TAAM
p.1601

Analysis of Sad Speech and Neutral-Sad Speech Conversion
p.1605

Analytic Hierarchy Process Method Based on the Cask Theory
p.1610

Application and Research on Distributed Collaborative Filtering Recommendation Algorithm Based on Hadoop
p.1615

Application of Comprehensive Evaluation and Sensitive Analysis in Certain Equipment
p.1622

Application of Legendre Polynomial in Predicting Total Energy Consumption
p.1627

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Analysis of Sad Speech and Neutral-Sad Speech...

Analysis of Sad Speech and Neutral-Sad Speech Conversion

Abstract:

A parameter mapping model to convert neutral speech to sad speech was proposed in this paper by comparison of statistical parameters between neutral and sad speech sample pairs with the same text content. In this model, we found sad speech with generally lower fundamental frequency than neutral speech, and the F0 contour is more stable than neutral speech; while the formants of sad speech is slightly higher than neutral speech. When concerning rhythm, the speed of sad speech is slightly slower than neutral speech. There exists significant difference between voiced segments and voiceless segments. Voiceless segments are significantly longer in sad speech. Speech conversion from neutral to sad was realized using this model, and got good results.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

1605-1609

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.1605

Citation:

Cite this paper

Online since:

January 2015

Authors:

Ya Hui Hou, Xiao Yue Ma, Rui Yuan, Zhong Zhe Xiao*

Keywords:

Emotional Speech, Speech Conversion

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Picard, R., Affective Computing, MIT Press, (1997).

Google Scholar

[2] Ling Cen; Chan, P.; Minghui Dong; Haizhou Li, Generating emotional speech from neutral speech, 7th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2010, pp.383-386.

DOI: 10.1109/iscslp.2010.5684862

Google Scholar

[3] Haojie Zhang; Yong Yang, Fundamental frequency adjustment and formant transition based emotional speech synthesis, 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2012, pp.1797-1801.

DOI: 10.1109/fskd.2012.6234018

Google Scholar

[4] Xiao, Z., Dellandrea, E., Dou, W., Chen, Ambiguous classification of emotional speech, International Workshop on EMOTION – satellite of International Conference on Language Resources and Evaluation (LREC), (2008).

Google Scholar

[5] Burkhardt F, Paeschke A, Rolfes M, et al., A database of German emotional speech, Interspeech, 2005, 5: 1517-1520.

DOI: 10.21437/interspeech.2005-446

Google Scholar