4 papers
StuPASE: Towards Low-Hallucination Studio-Quality Generative Speech Enhancement
Xiaobin Rong, Jun Gao, Zheng Wang +3
Achieving high perceptual quality without hallucination remains a challenge in generative speech enhancement (SE). A representative approach, PASE, is robust to hallucination but h…
PASE: Leveraging the Phonological Prior of WavLM for Low-Hallucination Generative Speech Enhancement
Xiaobin Rong, Qinwen Hu, Mansur Yesilbursa +2
Generative models have shown remarkable performance in speech enhancement (SE), achieving superior perceptual quality over traditional discriminative approaches. However, existing…
Low-Resource Audio Codec (LRAC): 2025 Challenge Description
Kamil Wojcicki, Yusuf Ziya Isik, Laura Lechler +8
While recent neural audio codecs deliver superior speech quality at ultralow bitrates over traditional methods, their practical adoption is hindered by obstacles related to low-res…
Assessing speech quality metrics for evaluation of neural audio codecs under clean speech conditions
Wolfgang Mack, Nezih Topaloglu, Laura Lechler +5
Objective speech-quality metrics are widely used to assess codec performance. However, for neural codecs, it is often unclear which metrics provide reliable quality estimates. To a…