Acoustic surveillance for respiratory diseases: a prospective analysis of cough trends using artificial intelligence.

Syndromic surveillance for respiratory disease is limited by an inability to monitor its protean manifestation, cough. Advances in artificial intelligence provide the ability to passively monitor cough at individual and community levels. We hypothesized that changes in the aggregate number of coughs recorded among a sample could serve as a lead indicator for population incidence of respiratory diseases, particularly that of COVID-19. We enrolled over 900 people from the city of Pamplona (Spain) between 2020 and 2021 and used artificial intelligence cough detection software to monitor their cough. We collected nine person-years of cough aggregated data. Coughs per hour surged around the time cohort subjects sought medical care. There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population. We propose that a clearer correlation with COVID-19 incidence could be achieved with better penetration and compliance with cough monitoring.

Illegal Logging Detection Based on Acoustic Surveillance of Forest

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 algorithms were tested. Experimental setups, using different ratios of sound-to-noise values, were followed and the best classification accuracy was reported by the support vector machine algorithm. In addition, a postprocessing scheme on decision level was applied that provided an improvement in the performance of more than 1%, mainly in cases of low ratios of sound-to-noise. Finally, we evaluated a late-stage fusion method, combining the postprocessed recognition results of the three top-performing classifiers, and the experimental results showed a further improvement of approximately 2%, in terms of absolute improvement, with logging sound recognition accuracy reaching 94.42% when the ratio of sound-to-noise was equal to 20 dB.

Cicero the Barbarian

Late Into The Night, I Sit Alone in My Study, Listening. in This, I Am Not Unlike The Title Character of Italo Calvino's “A King Listens,” one of three stories that make up his Under a Jaguar Sun, first published as a collection in 1986. The aim of Calvino's king is the acoustic surveillance of his realm, every corner of which is connected to the throne room by a twisting network of resonant tubes. Day in, day out, he listens, learning much, but feeling very little.This royal listener would later capture the imagination of the philosopher Adriana Cavarero, who opens her book For More than One Voice with a close reading of the story. For Cavarero, Calvino's king is very much like philosophy in its traditional Western form, listening for bodiless, universal logos, the Greek word for “word” that ancient philosophy uses to designate the rational order of the cosmos. In the story, the king is brought to his knees, suddenly and unexpectedly, by the sound of a woman singing. For Cavarero, this single, singular voice embodies the particularity that philosophy traditionally excludes in the name of the universal.