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We formulated non-speech vocalization (NSV) modeling as a text-to-speech taskand verified its viability. Specifically, we evaluated the phoneticexpressivity of HUBERT speech units on NSVs and verified our model's ability tocontrol over speaker timbre even though the training data is speaker few-shot.In addition, we substantiated that the heterogeneity in recording conditions isthe major obstacle for NSV modeling. Finally, we discussed five improvementsover our method for future research. Audio samples of synthesized NSVs areavailable on our demo page: https://resemble-ai.github.io/reLaugh.

Synthesizing Personalized Non-speech Vocalization from Discrete Speech Representations