Next Article in Journal
Use of Terrestrial Laser Scanning Technology for Long Term High Precision Deformation Monitoring
Previous Article in Journal
Molecular Sensing by Nanoporous Crystalline Polymers
Article Menu

Export Article

Open AccessArticle
Sensors 2009, 9(12), 9858-9872;

Application of Poincare-Mapping of Voiced-Speech Segments for Emotion Sensing

Institute of Electronics, Technical University of Lodz, Poland, Wolczanska 213/215, 90-924 Lodz, Poland
Division of Electrical, Electronics and Computer Engineering, Chonbuk National University, 561-756 Chonju, Korea
Author to whom correspondence should be addressed.
Received: 30 October 2009 / Revised: 14 November 2009 / Accepted: 17 November 2009 / Published: 3 December 2009
(This article belongs to the Section Chemical Sensors)
Full-Text   |   PDF [372 KB, uploaded 21 June 2014]


The following paper introduces a group of novel speech-signal descriptors that reflect phoneme-pronunciation variability and that can be considered as potentially useful features for emotion sensing. The proposed group includes a set of statistical parameters of Poincare maps, derived for formant-frequency evolution and energy evolution of voiced-speech segments. Two groups of Poincare-map characteristics were considered in the research: descriptors of sample-scatter, which reflect magnitudes of phone-uttering variations and descriptors of cross-correlations that exist among samples and that evaluate consistency of variations. It has been shown that inclusion of the proposed characteristics into the pool of commonly used speech descriptors, results in a noticeable increase—at the level of 10%—in emotion sensing performance. Standard pattern recognition methodology has been adopted for evaluation of the proposed descriptors, with the assumption that three- or four-dimensional feature spaces can provide sufficient emotion sensing. Binary decision trees have been selected for data classification, as they provide with detailed information on emotion-specific discriminative power of various speech descriptors. View Full-Text
Keywords: emotion sensing; feature selection; Poincare-maps; decision-trees emotion sensing; feature selection; Poincare-maps; decision-trees
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Ślot, K.; Bronakowski, Ł.; Cichosz, J.; Kim, H. Application of Poincare-Mapping of Voiced-Speech Segments for Emotion Sensing. Sensors 2009, 9, 9858-9872.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top