ICASSP 2023 Deep Noise Suppression Challenge - Dubey, Harishchandra; Gopal, Vishak; Cutler, Ross; Aazami, Ashkan; Matusevych, Sergiy; Braun, Sebastian; Eskimez, Sefik Emre; Thakker, Manthan; Yoshioka, Takuya; Gamper, Hannes; Aichner, Robert (IEEE Open Journal of Signal Processing, 2023)
The ICASSP 2023 Deep Noise Suppression (DNS) Challenge marks the fifth edition of the DNS challenge series. DNS challenges were organized from 2019 to 2023 to foster research in the field of DNS. Previous DNS challenges were held at INTERSPEECH 2020, ICASSP 2021, INTERSPEECH 2021, and ICASSP 2022. This challenge aims to advance models capable of jointly addressing denoising, dereverberation, and interfering talker suppression, with separate tracks focusing on headset and speakerphone scenarios. The challenge facilitates personalized deep noise suppression by providing accompanying enrollment clips for each test clip, each containing the primary talker only, which can be used to compute a speaker identity feature and disentangle primary and interfering speech. While the majority of models submitted to the challenge were personalized, the same teams emerged as the winners in both tracks. The best models demonstrated improvements of 0.145 and 0.141 in the challenge's score, respectively, when compared to the noisy blind test set. We present additional analysis and draw comparisons to previous challenges.