论文标题
ICASSP 2022声学回声取消挑战
ICASSP 2022 Acoustic Echo Cancellation Challenge
论文作者
论文摘要
ICASSP 2022声学回声取消挑战旨在刺激声学回声取消(AEC)的研究,这是言语增强的重要领域,并且仍然是音频通信的首要问题。这是第三次AEC挑战,它可以通过包括移动方案,在挑战目标指标中增加语音识别率以及使默认的样本率为48 kHz来增强。在这项挑战中,我们开源了两个大型数据集,以在单一谈话和双重谈话方案下培训AEC模型。这些数据集由来自实际环境中的10,000多个真实音频设备和人说的录音以及合成数据集组成。我们还开源了一个在线主观测试框架,并为研究人员提供了在线客观指标服务,以快速测试其结果。这项挑战的获胜者是根据在所有不同的单一谈话和双重谈话方案以及语音识别单词接受率中获得的平均平均意见分数选择的。
The ICASSP 2022 Acoustic Echo Cancellation Challenge is intended to stimulate research in acoustic echo cancellation (AEC), which is an important area of speech enhancement and still a top issue in audio communication. This is the third AEC challenge and it is enhanced by including mobile scenarios, adding speech recognition rate in the challenge goal metrics, and making the default sample rate 48 kHz. In this challenge, we open source two large datasets to train AEC models under both single talk and double talk scenarios. These datasets consist of recordings from more than 10,000 real audio devices and human speakers in real environments, as well as a synthetic dataset. We also open source an online subjective test framework and provide an online objective metric service for researchers to quickly test their results. The winners of this challenge are selected based on the average Mean Opinion Score achieved across all different single talk and double talk scenarios, and the speech recognition word acceptance rate.