# A generative framework for conversational laughter: Its 'language model' and laughter sound synthesis

arXiv: https://arxiv.org/abs/2306.03465 · HTML: https://mlsanity.com/paper/2306.03465/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jun 2023.

## Built on by (most cited first, 1 of 1)

- [Towards human-like spoken dialogue generation between AI agents from written dialogue](https://mlsanity.com/paper/2310.01088/) (2023)

## Abstract (arXiv)

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.