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Dynamic visual features for audio-visual speaker verification

机译：动态视觉功能，用于视听扬声器验证

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摘要

The cascading appearance-based (CAB) feature extraction technique has established itself as the state-of-the-art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the visual speech recognition application also provide similar improvements for visual speaker recognition. A further study is conducted comparing synchronous HMM (SHMM) based fusion of CAB visual features and traditional perceptual linear predictive (PLP) acoustic features to show that higher complexity inherit in the SHMM approach docs not appear to provide any improvement in the final audio-visual speaker verification system over simpler utterance level score fusion.
机译：基于级联外观的（CAB）特征提取技术已成为提取动态视觉语音特征进行语音识别的最新技术。在本文中，我们将重点研究该技术在相关说话人验证应用中的有效性。通过研究级联每个阶段的说话人验证能力，我们将证明减少视觉语音识别应用程序的静态说话人和环境信息的相同步骤也为视觉说话人识别提供了类似的改进。进行了进一步的研究，比较了基于同步HMM（SHMM）的CAB视觉特征与传统感知线性预测（PLP）声学特征的融合，以显示SHMM方法文档中继承的较高复杂性似乎无法为最终的视听提供任何改进说话人验证系统，通过更简单的话语水平得分融合。

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