ConferencingSpeech 2022

With the advances in speech communication systems such as online conferencing applications, we can seamlessly work with people regardless where they are. However, during the meeting, the speech quality is significantly affected by background noise, reverberation, packet loss, network jitter and many other factors. Therefore, an effective objective assessment approach is needed to evaluate or monitor the speech quality of the ongoing call. If severely degraded speech quality is detected, then the statistical information could be shared with the service provider in time. This enables the service provider to find out the root cause and improve the speech quality to guarantee better user experience in the future. Although the performance of objective speech quality assessment methods has been improved dramatically over the past few decades, there are still a set of open research problems that should be further addressed for the real-time speech communication systems, especially the challenge of non-intrusive speech assessment. ConferencingSpeech 2022 challenge is proposed to stimulate research in the areas mentioned above. This challenge will provide comprehensive training datasets, a comprehensive test dataset and a baseline system. The final ranking of this challenge will be decided by the predicted accuracy of the MOS scores from the submitted model or algorithm on the test dataset.