Next Article in Journal
Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm
Previous Article in Journal
Motion Field Estimation for a Dynamic Scene Using a 3D LiDAR
Open AccessArticle

The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

Department of Information Technology & Communication, Shih Chien University, 200 University Road, Neimen, Kaohsiung 84550, Taiwan
Sensors 2014, 14(9), 16692-16714; https://doi.org/10.3390/s140916692
Received: 9 June 2014 / Revised: 24 August 2014 / Accepted: 29 August 2014 / Published: 9 September 2014
(This article belongs to the Section Physical Sensors)
In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS). This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII) derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB) and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB), to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM) as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D) TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech. View Full-Text
Keywords: emotional feature extraction; emotion sensing; spectrogram; texture image information emotional feature extraction; emotion sensing; spectrogram; texture image information
MDPI and ACS Style

Wang, K.-C. The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech. Sensors 2014, 14, 16692-16714.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Back to TopTop