7 citations · 7 across the 5 of their papers we have counts for
5 papers
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 +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…
MUSHRA-1S: A scalable and sensitive test approach for evaluating top-tier speech processing systems
Laura Lechler, Ivana Balic
Evaluating state-of-the-art speech systems necessitates scalable and sensitive evaluation methods to detect subtle but unacceptable artifacts. Standard MUSHRA is sensitive but lack…
Crowdsourcing MUSHRA Tests in the Age of Generative Speech Technologies: A Comparative Analysis of Subjective and Objective Testing Methods
Laura Lechler, Chamran Moradi, Ivana Balic
The MUSHRA framework is widely used for detecting subtle audio quality differences but traditionally relies on expert listeners in controlled environments, making it costly and imp…
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…