{"id":590,"date":"2020-12-17T19:28:13","date_gmt":"2020-12-17T17:28:13","guid":{"rendered":"http:\/\/members.loria.fr\/ADeleforge\/?p=590"},"modified":"2021-09-22T12:03:52","modified_gmt":"2021-09-22T10:03:52","slug":"acoust-ia-making-acoustic-diagnosis-better-simpler-and-cheaper","status":"publish","type":"post","link":"https:\/\/members.loria.fr\/ADeleforge\/acoust-ia-making-acoustic-diagnosis-better-simpler-and-cheaper\/","title":{"rendered":"Acoust.IA : Making Acoustic Diagnosis Better, Simpler and Cheaper"},"content":{"rendered":"

\"\"<\/a>October 1st 2020 marked the start of ACOUST.IA<\/strong>, an Inria-funded 3 years collaborative projects jointly lead by my collaborator C\u00e9dric Foy from the acoustic research team UMRAE<\/a> at the Cerema of Strasbourg<\/a> and myself. Our goal is to develop new techniques at the intersection of acoustics, audio signal processing and machine learning, to make the acoustic diagnosis of rooms better, simpler and cheaper. The core question is: \u00ab\u00a0Can one retrieve the acoustical properties of surfaces inside a room, such as their absorption coefficients, from the audio recordings of a few claps?\u00a0\u00bb.\u00a0 <\/em>St\u00e9phane Dilungana just started his PhD thesis in Strasbourg on this topic, and is co-supervized by me, C\u00e9dric, and Sylvain Faisan<\/a> from the laboratory iCube<\/a> of the University of Strasbourg.<\/p>\n

 <\/p>\n

<\/p>\n

Click here<\/a> for a general audience article on the project, and here is a video report on the project made by the regional TV channel France 3 Lorraine<\/a>:<\/p>\n\n\n