The DCASE (Detection and Classification of Acoustic Scenes and Events) community has had a substantial role in the recent growth of the research interest towards the audio content analysis of everyday environments. The community organizes two major events annually: DCASE Challenge, an evaluation campaign to benchmark the progress in the field, and  DCASE Workshop, a venue to publish and discuss scientific output. Through these, the community offers a strong platform for discussion of the different perspectives and approaches, from algorithm development to practical applications. The members of the community have a broad background, from academic research to commercial research and development. The Audio Research Group (ARG) of Tampere University (TAU), led by professor Tuomas Virtanen, has been strongly involved in creating the community. The group has organized DCASE Workshops (in 2016 and 2017), and each DCASE Challenge since 2016 has included multiple evaluation tasks organized by the researchers from the group.

The goal of the sound event localization and detection task is to recognize individual sound events of specific classes, detect their temporal activity and estimate their location during the activity [3]. The main challenges in the task are the interfering directional events not belonging to the target classes, as well as spatial ambient noise always present in the acoustic environment. Input to the SELD system is multi-channel audio, captured with a microphone array, and the system output is the estimated sound event activity together with the spatial location of the event (elevation and azimuth). The task uses simulated scene recordings with dynamically moving target sound sources and interfering sound sources. The recordings are generated with isolated sound event samples and real measured room impulse responses.

The SELD task is a relatively new research topic, and it has been part of the DCASE Challenge only in the three most recent editions. The difficulty of the task has been increased in each edition by making the setup more realistic. In the first edition (DCASE2019), the setup consisted of two static sound sources in the acoustic environment with low reverberation times. In the second edition (DCASE2020), the setup was made more challenging with increased reverberation times, added ambient noise, and dynamically moving sound sources. This year the complexity of the setup was increased further by having three moving sound sources and non-target sound sources in the scene. For system development, 10-hour annotated audio data in one-minute long scene recordings was provided and the challenge evaluation was done on 3 hours of audio data (one-minute recordings) without any metadata. In total there were 13 different simulated acoustic environments. The task received 36 system submissions from 12 international research teams. As the task setup has become more challenging over the years, the submitted solutions have moved from approaches doing separate sound event detection and localization towards joint architectures where sounds are localized and detected simultaneously. Currently, the best-performing systems are showing an impressive level of performance which is already suitable for some practical applications. Detailed results can be viewed on the task result page at the DCASE website.