在人機語音交互系統中，機器不僅要具有理解人類語音的能力，還應當具有識別說話人情感的能力。本文提出了基于高斯混合模型(GMM)的序列分類和識別的改進方法，并將該方法引入到語音情感識別的研究中。本文提出了觀測值次序均衡的方法。實驗結果證明這種新的方法有效地提高了語音情感識別的準確率。
關鍵詞：語音序列分類；語音情感識別；GMM評分函數

EMOTION CLASSIFICATION AND RECOGNITION OF SPEECH? USING GMM-BASED METHOD HUANG Feng, YIN Jun-xun (School of Elec.&Info. Engg., South China Univ. of Technology, Guangzhou 510640,China) Abstract: For human-machine speech interaction system, machine should not only have the ability to understand contents of human speech, but should also be able to recognize human emotion from input speech to perform properly. In this paper we improve the sequence classification and recognition method based on GMM scoring and score space mapping, and use the new method for speech emotion classification. We propose order compensation method for improvement. Experiment results show the new method significantly improves accuracy of emotion classification and recognition in speech.
Key words: Speech sequential classification, emotion recognition, GMM scoring