4 papers
Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering
Cheng-Kuang Chang, Kai-Wei Chang, Alexander H. Liu +1
Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the internal mechanism by which they coor…
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Alexander H. Liu, Sang-gil Lee, Chao-Han Huck Yang +5
Pre-training and representation learning have been playing an increasingly important role in modern speech processing. Nevertheless, different applications have been relying on dif…
A Closer Look at Neural Codec Resynthesis: Bridging the Gap between Codec and Waveform Generation
Alexander H. Liu, Qirui Wang, Yuan Gong +1
Neural Audio Codecs, initially designed as a compression technique, have gained more attention recently for speech generation. Codec models represent each audio frame as a sequence…
Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models
Haibin Wu, Xuanjun Chen, Yi-Cheng Lin +13
Neural audio codec models are becoming increasingly important as they serve as tokenizers for audio, enabling efficient transmission or facilitating speech language modeling. The i…