图 书 馆
建模说话人内部的变异性以提高说话人识别度Modelling Intra-Speaker Variability for Improved Speaker Recognition |
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| 课程网址: | http://videolectures.net/slsfs05_aronowitz_misvi/ |
| 主讲教师: | Hagai Aronowitz |
| 开课单位: | 巴伊兰大学 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper we present a speaker recognition algorithm that models explicitly intra-speaker inter-session variability. Such variability, which is caused by channel, noise and temporary speaker characteristics (mood, fatigue, etc.), is not modeled explicitly by the state-of-the-art speaker recognition algorithms. We define a session-space in which each session (either train or test spoken utterance) is a vector. We then calculate a rotation of the session-space for which the estimated intra-speaker subspace is trivially isolated and can be modeled explicitly. Due to the high dimensionality of the session-space, it is impossible to use standard orthogonalization methods. We therefore used QR factorization based on Givens rotations to calculate the projection. On the NIST-2004 evaluation corpus, recognition error rate was reduced by 23% compared to the classic GMM state-of-the-art algorithm. |
| 关 键 词: | 说话人识别算法; 显式建模; 会话空间 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 38 |