Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226051760> ?p ?o ?g. }
- W4226051760 endingPage "e13152" @default.
- W4226051760 startingPage "e13152" @default.
- W4226051760 abstract "Animal vocalisations and natural soundscapes are fascinating objects of study, and contain valuable evidence about animal behaviours, populations and ecosystems. They are studied in bioacoustics and ecoacoustics, with signal processing and analysis an important component. Computational bioacoustics has accelerated in recent decades due to the growth of affordable digital sound recording devices, and to huge progress in informatics such as big data, signal processing and machine learning. Methods are inherited from the wider field of deep learning, including speech and image processing. However, the tasks, demands and data characteristics are often different from those addressed in speech or music analysis. There remain unsolved problems, and tasks for which evidence is surely present in many acoustic signals, but not yet realised. In this paper I perform a review of the state of the art in deep learning for computational bioacoustics, aiming to clarify key concepts and identify and analyse knowledge gaps. Based on this, I offer a subjective but principled roadmap for computational bioacoustics with deep learning: topics that the community should aim to address, in order to make the most of future developments in AI and informatics, and to use audio data in answering zoological and ecological questions." @default.
- W4226051760 created "2022-05-05" @default.
- W4226051760 creator A5005866826 @default.
- W4226051760 date "2022-03-21" @default.
- W4226051760 modified "2023-10-14" @default.
- W4226051760 title "Computational bioacoustics with deep learning: a review and roadmap" @default.
- W4226051760 cites W1514601846 @default.
- W4226051760 cites W1568645074 @default.
- W4226051760 cites W1587644769 @default.
- W4226051760 cites W1865871504 @default.
- W4226051760 cites W1901129140 @default.
- W4226051760 cites W1990093930 @default.
- W4226051760 cites W2001537489 @default.
- W4226051760 cites W2006614119 @default.
- W4226051760 cites W2011606961 @default.
- W4226051760 cites W2012685917 @default.
- W4226051760 cites W2029953487 @default.
- W4226051760 cites W2034151396 @default.
- W4226051760 cites W2047918105 @default.
- W4226051760 cites W2064675550 @default.
- W4226051760 cites W2078685049 @default.
- W4226051760 cites W2112796928 @default.
- W4226051760 cites W2154592455 @default.
- W4226051760 cites W2257512788 @default.
- W4226051760 cites W2299408279 @default.
- W4226051760 cites W2408239454 @default.
- W4226051760 cites W2461650116 @default.
- W4226051760 cites W2518102674 @default.
- W4226051760 cites W2555915854 @default.
- W4226051760 cites W2566527146 @default.
- W4226051760 cites W2566710071 @default.
- W4226051760 cites W2566783773 @default.
- W4226051760 cites W2606461235 @default.
- W4226051760 cites W2622859419 @default.
- W4226051760 cites W2761083049 @default.
- W4226051760 cites W2761494123 @default.
- W4226051760 cites W2764338498 @default.
- W4226051760 cites W2770670413 @default.
- W4226051760 cites W2772345051 @default.
- W4226051760 cites W2789494826 @default.
- W4226051760 cites W2793008329 @default.
- W4226051760 cites W2794193469 @default.
- W4226051760 cites W2809169812 @default.
- W4226051760 cites W2883595988 @default.
- W4226051760 cites W2886674542 @default.
- W4226051760 cites W2888678380 @default.
- W4226051760 cites W2889994223 @default.
- W4226051760 cites W2894955409 @default.
- W4226051760 cites W2907755528 @default.
- W4226051760 cites W2912439585 @default.
- W4226051760 cites W2914034186 @default.
- W4226051760 cites W2916994621 @default.
- W4226051760 cites W2919115771 @default.
- W4226051760 cites W2921717508 @default.
- W4226051760 cites W2922355292 @default.
- W4226051760 cites W2936654294 @default.
- W4226051760 cites W2938440247 @default.
- W4226051760 cites W2942595104 @default.
- W4226051760 cites W2942893872 @default.
- W4226051760 cites W2951205366 @default.
- W4226051760 cites W2951661487 @default.
- W4226051760 cites W2962845248 @default.
- W4226051760 cites W2962894131 @default.
- W4226051760 cites W2965503177 @default.
- W4226051760 cites W2966508064 @default.
- W4226051760 cites W2970296326 @default.
- W4226051760 cites W2977689015 @default.
- W4226051760 cites W2981733351 @default.
- W4226051760 cites W2982703100 @default.
- W4226051760 cites W2983227958 @default.
- W4226051760 cites W2986884109 @default.
- W4226051760 cites W2990251032 @default.
- W4226051760 cites W2994125460 @default.
- W4226051760 cites W2996065641 @default.
- W4226051760 cites W2996692619 @default.
- W4226051760 cites W2998692524 @default.
- W4226051760 cites W2999187172 @default.
- W4226051760 cites W3000616311 @default.
- W4226051760 cites W3010719548 @default.
- W4226051760 cites W3012504141 @default.
- W4226051760 cites W3012624518 @default.
- W4226051760 cites W3012651379 @default.
- W4226051760 cites W3016210959 @default.
- W4226051760 cites W3017875707 @default.
- W4226051760 cites W3022198147 @default.
- W4226051760 cites W3024599079 @default.
- W4226051760 cites W3033723397 @default.
- W4226051760 cites W3036100825 @default.
- W4226051760 cites W3040972704 @default.
- W4226051760 cites W3041671906 @default.
- W4226051760 cites W3043884016 @default.
- W4226051760 cites W3088358114 @default.
- W4226051760 cites W3102534672 @default.
- W4226051760 cites W3105563334 @default.
- W4226051760 cites W3112740424 @default.
- W4226051760 cites W3121931845 @default.
- W4226051760 cites W3121989809 @default.
- W4226051760 cites W3126493952 @default.