3 papers
eess.AS2025
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…
cs.SD2024
Accelerating Codec-based Speech Synthesis with Multi-Token Prediction and Speculative Decoding
Tan Dat Nguyen, Ji-Hoon Kim, Jeongsoo Choi +4
The goal of this paper is to accelerate codec-based speech synthesis systems with minimum sacrifice to speech quality. We propose an enhanced inference method that allows for flexi…
eess.AS2024
Boosting Unknown-number Speaker Separation with Transformer Decoder-based Attractor
Younglo Lee, Shukjae Choi, Byeong-Yeol Kim +2
We propose a novel speech separation model designed to separate mixtures with an unknown number of speakers. The proposed model stacks 1) a dual-path processing block that can mode…