论文标题
扬声器二重关注的说话者和话语验证
Speaker-Utterance Dual Attention for Speaker and Utterance Verification
论文作者
论文摘要
在本文中，我们研究了一种新型技术，该技术利用说话者特征和语言内容之间的相互作用，以提高说话者的验证和话语验证性能。我们在统一的神经网络中实施了说话者 - 动物双重关注（SUDA）的想法。双重关注是指针对说话者和话语验证的两个任务的注意机制。拟议的Suda具有注意力面具机制，以了解扬声器和话语信息流之间的相互作用。这仅通过掩盖无关的对应物来重点关注所需的信息以进行各自任务。对RSR2015语料库进行的研究证实，拟议的Suda在没有注意力面罩的情况下优于该框架，以及用于说话者和话语验证的几个竞争系统。
In this paper, we study a novel technique that exploits the interaction between speaker traits and linguistic content to improve both speaker verification and utterance verification performance. We implement an idea of speaker-utterance dual attention (SUDA) in a unified neural network. The dual attention refers to an attention mechanism for the two tasks of speaker and utterance verification. The proposed SUDA features an attention mask mechanism to learn the interaction between the speaker and utterance information streams. This helps to focus only on the required information for respective task by masking the irrelevant counterparts. The studies conducted on RSR2015 corpus confirm that the proposed SUDA outperforms the framework without attention mask as well as several competitive systems for both speaker and utterance verification.
