We generalized a voice morphing algorithm capable of handling temporally variable, multiple-attributes, and multiple instances. The generalized morphing provides a new strategy for investigating speech diversity. However, excessive complexity and the difficulty of preparation have prevented researchers and students from enjoying its benefits. To address this issue, we introduced a set of interactive tools to make preparation and tests less cumbersome. These tools are integrated into our previously reported interactive tools as extensions. The introduction of the extended tools in lessons in graduate education was successful. Finally, we outline further extensions to explore excessively complex morphing parameter settings.

翻译：我们泛化了一种能够处理时间可变、多属性及多实例的语音变形算法。该泛化变形为探究语音多样性提供了新策略。然而，过度复杂性与准备工作的困难阻碍了研究人员与学生充分享受其益处。为解决此问题，我们引入了一套交互式工具以降低准备与测试的繁琐程度。这些工具作为扩展功能集成至我们先前报道的交互式工具中。该扩展工具在研究生教育课程中的引入取得了成功。最后，我们概述了进一步扩展的方向，以探索过度复杂的变形参数设置。