3 papers
cs.SD2026
Luna-TTS Family Technical Report
Feng Yin, Shuai Shi, Junjie Zheng +19
Modern text-to-speech (TTS) is dominated by autoregressive (AR) codec language models, whose left-to-right decoding brings latency that grows with utterance length, error accumulat…
cs.LG2025
DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration
Tianteng Gu, Bei Liu, Bo Xiao +3
Pruning is a widely used technique to compress large language models (LLMs) by removing unimportant weights, but it often suffers from significant performance degradation - especia…
eess.AS2024
Memory-Efficient Training for Deep Speaker Embedding Learning in Speaker Verification
Bei Liu, Yanmin Qian
Recent speaker verification (SV) systems have shown a trend toward adopting deeper speaker embedding extractors. Although deeper and larger neural networks can significantly improv…