Introduction

Welcome to Far-field Multi-channel Speech Enhancement Challenge for Video Conferencing (ConferencingSpeech 2021). With the advances in video conferencing technology, we are able to seamlessly connect with people of our choice anytime anywhere in the world. Video conferencing helps break barriers of distance among people. However, during video conference, the speech quality will be significantly affected by background noise, reverberation, number of recording microphones, the layout of microphone array, the acoustic and circuit design of microphone arrays, and so on. Effective speech enhancement plays an important role in the video conferencing system. Although the performance of speech enhancement has been improved dramatically in the past several decades, there are still a set of open research problems that should be further addressed in the far-field and complex meeting room environments, which includes but not limited to:

● Multi-channel speech enhancement with single microphone

   array

 

● Multi-channel speech enhancement with noisy and reverberant          environments

● Multi-channel speech enhancement with multiple distributed

   microphone arrays

 

● Multi-channel speech enhancement with low-latency and zero

   look-ahead (casual system)

ConferencingSpeech 2021 challenge is proposed to stimulate research in the areas mentioned above. Targeting the real video conferencing room application, the challenge database is recorded from real speakers. Number of speakers and distances between speakers and microphone arrays vary according to the sizes of meeting rooms. Multiple microphone arrays with different geometric topologies are allocated in each recording environment. The challenge will provide the list of training set, development set, scripts for simulation, and baseline systems for participants to develop their systems. The final ranking of the challenge will be decided by the subjective evaluation. The subjective evaluation will be performed using Absolute Category Ratings (ACR) to estimate a Mean Opinion Score (MOS) through Tencent Online Media Subjective Evaluation platform.

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