Learn More
This paper proposes a novel speech emotion recognition (SER) framework for affective interaction between human and personal devices. Most of the conventional SER techniques adopt a speaker-independent model framework because of the sparseness of individual speech data. However, a large amount of individual data can be accumulated on a personal device,(More)
This paper proposes a new Speech Emotion Recognition (SER) framework. Compared to the speaker-independent emotion models, speaker-adapted models constructed by using a speaker's emotional speech data can represent the speaker's emotional characteristics more precisely, thus improving SER accuracy. However, it is hard to collect a sufficient amount of(More)
  • 1