7 citations · 7 across the 5 of their papers we have counts for
4 papers · 1 filter
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…
Assessing speech quality metrics for evaluation of neural audio codecs under clean speech conditions
Wolfgang Mack, Nezih Topaloglu, Laura Lechler +4
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…
Crowdsourced Multilingual Speech Intelligibility Testing
Laura Lechler, Kamil Wojcicki
With the advent of generative audio features, there is an increasing need for rapid evaluation of their impact on speech intelligibility. Beyond the existing laboratory measures, w…