International audienceAn increasing number of researchers work in computational auditory scene analysis (CASA). However, a set of tasks, each with a well-defined evaluation framework and commonly used datasets do not yet exist. Thus, it is difficult for results and algorithms to be compared fairly, which hinders research on the field. In this paper we will introduce a newly-launched public evaluation challenge dealing with two closely related tasks of the field: acoustic scene classification and event detection. We give an overview of the tasks involved; describe the processes of creating the dataset; and define the evaluation metrics. Finally, illustrations on results for both tasks using baseline methods applied on this dataset are presen...
This paper presents the Real-Life Indoor Sound Event Dataset (ReaLISED), a new database which has be...
This paper presents a baseline system for automatic acoustic scene classification based on the audio...
This work was supported by the Centre for Digital Music Platform (grant EP/K009559/1) and a Leadersh...
An increasing number of researchers work in computational auditory scene analysis (CASA). However, a...
International audienceAn increasing number of researchers work in computational auditory scene analy...
This paper describes a newly-launched public evaluation challenge on acoustic scene classification a...
International audienceThis paper describes a newly-launched public evaluation challenge on acoustic ...
For intelligent systems to make best use of the audio modality, it is important that they can recogn...
Public evaluation campaigns and datasets promote active development in target research areas, allowi...
International audiencePublic evaluation campaigns and datasets promote active development in target ...
In this article, we present an account of the state of the art in acoustic scene classification (ASC...
International audience—For intelligent systems to make best use of the audio modality, it is importa...
Research work on automatic speech recognition and automatic music transcription has been around for ...
This book presents computational methods for extracting the useful information from audio signals, c...
This paper introduces a model of environmental acoustic scenes which adopts a morphological approach...
This paper presents the Real-Life Indoor Sound Event Dataset (ReaLISED), a new database which has be...
This paper presents a baseline system for automatic acoustic scene classification based on the audio...
This work was supported by the Centre for Digital Music Platform (grant EP/K009559/1) and a Leadersh...
An increasing number of researchers work in computational auditory scene analysis (CASA). However, a...
International audienceAn increasing number of researchers work in computational auditory scene analy...
This paper describes a newly-launched public evaluation challenge on acoustic scene classification a...
International audienceThis paper describes a newly-launched public evaluation challenge on acoustic ...
For intelligent systems to make best use of the audio modality, it is important that they can recogn...
Public evaluation campaigns and datasets promote active development in target research areas, allowi...
International audiencePublic evaluation campaigns and datasets promote active development in target ...
In this article, we present an account of the state of the art in acoustic scene classification (ASC...
International audience—For intelligent systems to make best use of the audio modality, it is importa...
Research work on automatic speech recognition and automatic music transcription has been around for ...
This book presents computational methods for extracting the useful information from audio signals, c...
This paper introduces a model of environmental acoustic scenes which adopts a morphological approach...
This paper presents the Real-Life Indoor Sound Event Dataset (ReaLISED), a new database which has be...
This paper presents a baseline system for automatic acoustic scene classification based on the audio...
This work was supported by the Centre for Digital Music Platform (grant EP/K009559/1) and a Leadersh...