Trends in audio scene source counting and analysis
Michael Nigro, Sridhar Krishnan · Machine Learning with Applications · 2024
Audio scene analysis involves a variety of tasks to obtain information from an audio environment. Audio source counting is one such task that has implications to many other aspects of audio analysis, yet it is relatively unexplored. This work presents the first review of the audio source counting literature and aims to convey the significance of this task to the wider domain of audio analysis. We identify and discuss connections between audio source counting and other more commonly studied audio analysis tasks. In addition, a review of the publicly available audio datasets is presented, highlighting the lack of datasets geared towards audio source counting. Our goal of this review paper is to promote future research of audio source counting. • Audio source counting determines the number of sound events in an audio recording. • Research shows audio source counting can help reduce errors in audio analysis. • A lack of audio source counting datasets and data standardization impedes research.