Sound Event Detection and Separation: a Benchmark on Desed Synthetic Soundscapes
| Autor: | Romain Serizel, Hakan Erdogan, Justin Salamon, Nicolas Turpault, John R. Hershey, Scott Wisdom, Eduardo Fonseca, Prem Seetharaman |
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| Přispěvatelé: | Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Google Inc, Research at Google, Universitat Pompeu Fabra [Barcelona] (UPF), Descript, Inc., Adobe Research, Part of this work was made with the support of the French National Research Agency, in the framework of the project LEAUDS 'Learning to understand audio scenes' (ANR-18-CE23-0020) and the French region Grand-Est. High Performance Computing resources were partially provided by the EXPLOR centre hosted by the University de Lorraine., Grid'5000, ANR-18-CE23-0020,LEAUDS,Apprentissage statistique pour la compréhension de scènes audio(2018), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Sound localization Sound (cs.SD) Reverberation Soundscape Computer science Speech recognition 02 engineering and technology Computer Science - Sound [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Audio and Speech Processing (eess.AS) Robustness (computer science) FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Sound (geography) synthetic soundscapes geography Signal processing geography.geographical_feature_category Event (computing) Sound event detection [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD] Benchmark (computing) sound separation 020201 artificial intelligence & image processing Electrical Engineering and Systems Science - Audio and Speech Processing |
| Zdroj: | ICASSP ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing ICASSP 2021-46th International Conference on Acoustics, Speech, and Signal Processing, Jun 2021, Toronto/Virtual, Canada. ⟨10.1109/ICASSP39728.2021.9414789⟩ |
| Popis: | International audience; We propose a benchmark of state-of-the-art sound event detection systems (SED). We designed synthetic evaluation sets to focus on specific sound event detection challenges. We analyze the performance of the submissions to DCASE 2021 task 4 depending on time related modifications (time position of an event and length of clips) and we study the impact of non-target sound events and reverberation. We show that the localization in time of sound events is still a problem for SED systems. We also show that reverberation and non-target sound events are severely degrading the performance of the SED systems. In the latter case, sound separation seems like a promising solution. |
| Databáze: | OpenAIRE |
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