Emotion Recognition Using Short Time Speech Analysis - Emotional Engineering - page 100

Fig. 10 Statistical analysis for emotion components with segment-level speech emotion analysis
for all speech samples
Recognizing the emotion of utterances is one of the more attractive topics in
speech analysis for human - computer interaction (HCI), healthcare, etc. However,
emotion strength analysis has been a very essential but dif ! cult research area. We
discussed the potential of using segment-level frames for such analysis. As shown
in Fig. 10 , the proposed method can indeed re fl ect the strengths of emotions in
utterance clusters over a short period of time. However, dif ! culties exist in applying
it to a single utterance because of the variances in the emotional components
regarding the utterances. Although additional research is necessary for collecting
more solid ! findings in terms of the emotion strength analysis of utterances, seg-
ment-level speech emotion analysis will be a new method for better recognizing
human emotion strength with machines.
7 Conclusion
An emotion recognition method using short time speech analysis was proposed. To
make the proposed method more ef ! cient and accurate, an advanced relative seg-
mentation method was introduced that uses correlation coef ! cients for ! fixed length
segment selection, which is essential for realizing the purely segment-level
approach. The proposed method can greatly increase the accuracy of emotion
recognition by more than 20 % compared with the conventional method of using
the global features of utterances, which was validated by using a database with
speech signals from 50 participates. The proposed method also showed the effec-
tiveness of determining the emotion strength of utterances over a period of time. It
can provide hints about emotion strength information according to our validation
results with the IAPS database.