10 papers
WAND: Windowed Attention and Knowledge Distillation for Efficient Autoregressive Text-to-Speech Models
Hanna Lee, Tan Dat Nguyen, Jaehoon Kang +1
Recent decoder-only autoregressive text-to-speech (AR-TTS) models produce high-fidelity speech, but their memory and compute costs scale quadratically with sequence length due to f…
MamTra: A Hybrid Mamba-Transformer Backbone for Speech Synthesis
Tan Dat Nguyen, Sangmin Bae, Joon Son Chung +1
Despite the remarkable quality of LLM-based text-to-speech systems, their reliance on autoregressive Transformers leads to quadratic computational complexity, which severely limits…
Social welfare optimisation under institutional reward and punishment
Van An Nguyen, Vuong Khang Huynh, Huu Loi Bui +8
Institutional incentives are widely used to promote cooperation among autonomous, self-regarding agents, from human societies to multi-agent and AI systems. Existing work typically…
MAGE: A Coarse-to-Fine Speech Enhancer with Masked Generative Model
The Hieu Pham, Tan Dat Nguyen, Phuong Thanh Tran +2
Speech enhancement remains challenging due to the trade-off between efficiency and perceptual quality. In this paper, we introduce MAGE, a Masked Audio Generative Enhancer that adv…
SPADE: Structured Pruning and Adaptive Distillation for Efficient LLM-TTS
Tan Dat Nguyen, Jaehun Kim, Ji-Hoon Kim +3
The goal of this paper is to introduce SPADE, a framework for Structured Pruning and Adaptive Distillation for Efficient Large Language Model-based text-to-speech (LLM-TTS). Recent…
Social welfare optimisation in well-mixed and structured populations
Van An Nguyen, Vuong Khang Huynh, Ho Nam Duong +10
Research on promoting cooperation among autonomous, self-regarding agents has often focused on the bi-objective optimisation problem: minimising the total incentive cost while maxi…