1 research outputs found
Research on several key technologies in practical speech emotion recognition
In this dissertation the practical speech emotion recognition technology is
studied, including several cognitive related emotion types, namely fidgetiness,
confidence and tiredness. The high quality of naturalistic emotional speech
data is the basis of this research. The following techniques are used for
inducing practical emotional speech: cognitive task, computer game, noise
stimulation, sleep deprivation and movie clips.
A practical speech emotion recognition system is studied based on Gaussian
mixture model. A two-class classifier set is adopted for performance
improvement under the small sample case. Considering the context information in
continuous emotional speech, a Gaussian mixture model embedded with Markov
networks is proposed.
A further study is carried out for system robustness analysis. First, noise
reduction algorithm based on auditory masking properties is fist introduced to
the practical speech emotion recognition. Second, to deal with the complicated
unknown emotion types under real situation, an emotion recognition method with
rejection ability is proposed, which enhanced the system compatibility against
unknown emotion samples. Third, coping with the difficulties brought by a large
number of unknown speakers, an emotional feature normalization method based on
speaker-sensitive feature clustering is proposed. Fourth, by adding the
electrocardiogram channel, a bi-modal emotion recognition system based on
speech signals and electrocardiogram signals is first introduced.
The speech emotion recognition methods studied in this dissertation may be
extended into the cross-language speech emotion recognition and the whispered
speech emotion recognition.Comment: in Chines