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Jonathan Miquel, Laurent Latorre and Simon Chamaillé-Jammes
Biologging refers to the use of animal-borne recording devices to study wildlife behavior. In the case of audio recording, such devices generate large amounts of data over several months, and thus require some level of processing automation for the raw d...
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Zakiya Azizah Cahyaningtyas, Diana Purwitasari, Chastine Fatichah
Pág. 21 - 34
Drum transcription is the task of transcribing audio or music into drum notation. Drum notation is helpful to help drummers as instruction in playing drums and could also be useful for students to learn about drum music theories. Unfortunately, transcrib...
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Fan Liu and Jiandong Fang
Classroom interactivity is one of the important metrics for assessing classrooms, and identifying classroom interactivity through classroom image data is limited by the interference of complex teaching scenarios. However, audio data within the classroom ...
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Oscar Sapena and Eva Onaindia
The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching...
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Vladimir Kulyukin
In 2014, we designed and implemented BeePi, a multi-sensor electronic beehive monitoring system. Since then we have been using BeePi monitors deployed at different apiaries in northern Utah to design audio, image, and video processing algorithms to analy...
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Giuseppe Ciaburro
Parking is a crucial element in urban mobility management. The availability of parking areas makes it easier to use a service, determining its success. Proper parking management allows economic operators located nearby to increase their business revenue....
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Loris Nanni, Sheryl Brahnam, Alessandra Lumini and Gianluca Maguolo
The classifier system proposed in this work combines the dissimilarity spaces produced by a set of Siamese neural networks (SNNs) designed using four different backbones with different clustering techniques for training SVMs for automated animal audio cl...
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Iosif Mporas, Isidoros Perikos, Vasilios Kelefouras and Michael Paraskevas
In this article, we present a framework for automatic detection of logging activity in forests using audio recordings. The framework was evaluated in terms of logging detection classification performance and various widely used classification methods and...
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Rigas Kotsakis, Maria Matsiola, George Kalliris and Charalampos Dimoulas
The current paper focuses on the investigation of spoken-language classification in audio broadcasting content. The approach reflects a real-word scenario, encountered in modern media/monitoring organizations, where semi-automated indexing/documentation ...
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Vasileios Bountourakis, Lazaros Vrysis, Konstantinos Konstantoudakis and Nikolaos Vryzas
Temporal feature integration refers to a set of strategies attempting to capture the information conveyed in the temporal evolution of the signal. It has been extensively applied in the context of semantic audio showing performance improvements against t...
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José Antonio Alves Menezes, Giordano Cabral, Bruno Gomes, Paulo Pereira
Pág. 14 - 35
To choice audio features has been a very interesting theme for audio classification experts. They have seen that this process is probably the most important effort to solve the classification problem. In this sense, there are techniques of Feature Learni...
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Safaa Alraddadi, Fahad Alqurashi, Georgios Tsaramirsis, Amany Al Luhaybi and Seyed M. Buhari
Variant approaches used to release scents in most recent olfactory displays rely on time for decision making. The applicability of such an approach is questionable in scenarios like video games or virtual reality applications, where the specific content ...
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Shinnosuke Isobe, Satoshi Tamura, Satoru Hayamizu, Yuuto Gotoh and Masaki Nose
Recently, automatic speech recognition (ASR) and visual speech recognition (VSR) have been widely researched owing to the development in deep learning. Most VSR research works focus only on frontal face images. However, assuming real scenes, it is obviou...
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Giuseppe Ciaburro and Gino Iannace
In recent years, security in urban areas has gradually assumed a central position, focusing increasing attention on citizens, institutions and political forces. Security problems have a different nature?to name a few, we can think of the problems derivin...
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Roberta Avanzato and Francesco Beritelli
An accurate estimate of rainfall levels is fundamental in numerous application scenarios: weather forecasting, climate models, design of hydraulic structures, precision agriculture, etc. An accurate estimate becomes essential to be able to warn of the im...
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Hwan Ing Hee, BT Balamurali, Arivazhagan Karunakaran, Dorien Herremans, Onn Hoe Teoh, Khai Pin Lee, Sung Shin Teng, Simon Lui and Jer Ming Chen
(1) Background: Cough is a major presentation in childhood asthma. Here, we aim to develop a machine-learning based cough sound classifier for asthmatic and healthy children. (2) Methods: Children less than 16 years old were randomly recruited in a Child...
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Mohammed Gamal Ragab, Said Jadid Abdulkadir, Norshakirah Aziz, Hitham Alhussian, Abubakar Bala and Alawi Alqushaibi
With the growth of deep learning in various classification problems, many researchers have used deep learning methods in environmental sound classification tasks. This paper introduces an end-to-end method for environmental sound classification based on ...
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Marc Ciufo Green and Damian Murphy
The classification of acoustic scenes and events is an emerging area of research in the field of machine listening. Most of the research conducted so far uses spectral features extracted from monaural or stereophonic audio rather than spatial features ex...
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Urszula Libal and Pawel Biernacki
An automatic honey bee classification system based on audio signals for tracking the frequency of workers and drones entering and leaving a hive.
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Sangwon Lee, Hyemi Kim and Gil-Jin Jang
Audio classification; music information retrieval; audio scene characterization; temporal localization of sound sources; audio indexing; audio surveillance systems; anomaly detection from audio sounds.
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