Deep Speech Enhancement Challenge is the 5th edition of deep noise suppression (DNS) challenges organized at ICASSP 2023 Signal Processing Grand Challenges. DNS challenges were organized during 2019-2023 to stimulate research in deep speech enhancement (DSE). Previous DNS challenges were organized at INTERSPEECH 2020, ICASSP 2021, INTERSPEECH 2021, and ICASSP 2022. From prior editions, we learnt that improving signal quality (SIG) is challenging particularly in presence of simultaneously active interfering talkers and noise. This challenge aims to develop models for joint denosing, dereverberation and suppression of interfering talkers. When primary talker wears a headphone, certain acoustic properties of their speech such as direct-to-reverberation (DRR), signal to noise ratio (SNR) etc. make it possible to suppress neighboring talkers even without enrollment data for primary talker. This motivated us to create two tracks for this challenge: (i) Track-1 Headset; (ii) Track-2 Speakerphone. Both tracks has fullband (48kHz) training data and testset, and each testclips has a corresponding enrollment data (10-30s duration) for primary talker. Each track invited submissions of personalized and non-personalized models all of which are evaluated through same subjective evaluation. Most models submitted to challenge were personalized models, same team is winner in both tracks where the best models has improvement of 0.145 and 0.141 in challenge's Score as compared to noisy blind testset.

翻译：深度语音增强挑战赛是ICASSP 2023信号处理大挑战赛中组织的第五届深度噪声抑制（DNS）挑战赛。DNS挑战赛于2019-2023年间举办，旨在推动深度语音增强（DSE）研究。此前DNS挑战赛分别于INTERSPEECH 2020、ICASSP 2021、INTERSPEECH 2021及ICASSP 2022期间举办。从往届经验中我们发现，在存在同时活动的干扰说话者与噪声的情况下，提升信号质量（SIG）尤为困难。本次挑战赛旨在开发用于联合去噪、去混响及抑制干扰说话者的模型。当主说话者佩戴耳机时，其语音的某些声学特性（如直达混响比DRR、信噪比SNR等）使得即便没有主说话者的注册数据，也能抑制邻近说话者。这一发现促使我们设立两个赛道：（i）赛道1-头戴式耳机；（ii）赛道2-免提电话。两个赛道均提供全频段（48kHz）训练数据与测试集，且每个测试片段均包含对应主说话者的注册数据（时长10-30秒）。各赛道接受个性化与非个性化模型提交，所有模型均通过相同的主观评估进行评价。提交至挑战赛的模型多为个性化模型，同一团队在两个赛道中均夺得冠军，其最佳模型相较含噪盲测测试集在挑战赛评分上分别提升了0.145和0.141。