对话中笑声的生成框架：其“语言模型”与笑声声音合成
A generative framework for conversational laughter: Its 'language model' and laughter sound synthesis
AI总结：
本文提出一种利用情感维度作为上下文、由笑声音素生成器和声音合成器组成的生成模型，以高可控方式合成多样且逼真的对话笑声，实验证明基于情感条件化能有效控制感知情感。
摘要：
由于对话中笑声的语音和声学表现高度多样，笑声合成应能够适应这种多样性，同时保持高可控性。本文提出了一种对话中笑声的生成模型，该模型利用情感维度作为对话上下文，能够产生多种多样的笑声。该模型包含两个部分：笑声“音素生成器”，它为给定的说话人ID和情感状态生成各种但逼真的笑声成分组合；以及笑声“声音合成器”，它接收笑声音素序列并产生反映说话人个性和情感状态的声学特征。听力实验结果表明，将音素生成器和声音合成器都基于情感维度进行条件设置，在合成笑声中对感知情感的控制最为有效。
英文摘要：
As the phonetic and acoustic manifestations of laughter in conversation are highly diverse, laughter synthesis should be capable of accommodating such diversity while maintaining high controllability. This paper proposes a generative model of laughter in conversation that can produce a wide variety of laughter by utilizing the emotion dimension as a conversational context. The model comprises two parts: the laughter "phones generator," which generates various, but realistic, combinations of laughter components for a given speaker ID and emotional state, and the laughter "sound synthesizer," which receives the laughter phone sequence and produces acoustic features that reflect the speaker's individuality and emotional state. The results of a listening experiment indicated that conditioning both the phones generator and the sound synthesizer on emotion dimensions resulted in the most effective control of the perceived emotion in synthesized laughter.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
