Crowdsourcing approach for subjective evaluation of echo impairment
| Autor: | Ross Cutler, Ando Saabas, Sten Sootla, Babak Nadari, Markus Loide |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Signal processing Sound (cs.SD) Computer science business.industry media_common.quotation_subject Speech recognition Echo (computing) Crowdsourcing Communications system Computer Science - Sound Audio and Speech Processing (eess.AS) FOS: Electrical engineering electronic engineering information engineering Quality (business) business PESQ media_common Electrical Engineering and Systems Science - Audio and Speech Processing |
| Zdroj: | ICASSP |
| DOI: | 10.48550/arxiv.2010.13063 |
| Popis: | The quality of acoustic echo cancellers (AECs) in real-time communication systems is typically evaluated using objective metrics like ERLE [1] and PESQ [2], and less commonly with lab-based subjective tests like ITU-T Rec. P.831 [3]. We will show that these objective measures are not well correlated to subjective measures. We then introduce an open-source crowdsourcing approach for subjective evaluation of echo impairment which can be used to evaluate the performance of AECs. We provide a study that shows this tool is highly reproducible. This new tool has been recently used in the ICASSP 2021 AEC Challenge [4] which made the challenge possible to do quickly and cost effectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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