Perceptual Effects of Dynamic Range Compression in Popular Music Recordings - January 2014
Accurate Calculation of Radiation and Diffraction from Loudspeaker Enclosures at Low Frequency - June 2013
New Measurement Techniques for Portable Listening Devices: Technical Report - October 2013
Collaborative Annotation Platform for Audio Semantics
In the majority of audio classification tasks that involve supervised machine learning, ground truth samples are regularly required as training inputs. Most researchers in this field usually annotate audio content by hand and for their individual requirements. This practice resulted in the absence of solid datasets and consequently research conducted by different researchers on the same topic cannot be effectively pulled together and elaborated on. A collaborative audio annotation platform is proposed for both scientific and application oriented audio-semantic tasks. Innovation points include easy operation and interoperability, on the fly annotation while playing audio content online, efficient collaboration with feature engines and machine learning algorithms, enhanced interaction, and personalization via state of the art Web 2.0 /3.0 services.
Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.