頁籤選單縮合
| 題 名 | Emotional Recognition Using a Compensation Transformation in Speech Signal |
|---|---|
| 作 者 | Zou, Cairong; Zhao, Yan; Zhao, Li; Zhen, Wenming; Bao, Yongqiang; | 書刊名 | International Journal of Computational Linguistics & Chinese Language Processing |
| 卷 期 | 12:1 2007.03[民96.03] |
| 頁 次 | 頁79-90 |
| 分類號 | 312.85 |
| 關鍵詞 | Speech emotional recognition; SER; GMM; Emotion recognition; Compensation transformation; |
| 語 文 | 英文(English) |
| 英文摘要 | An effective method based on GMM is proposed in this paper for speech emotional recognition; a compensation transformation is introduced in the recognition stage to reduce the influence of variations in speech characteristics and noise. The extraction of emotional features includes the globe feature, time series structure feature, LPCC, MFCC and PLP. Five human emotions (happiness, angry, surprise, sadness and neutral) are investigated. The result shows that it can increase the recognition ratio more than normal GMM; the method in this paper is effective and robust. |
本系統中英文摘要資訊取自各篇刊載內容。