Classification Of Spontaneous And Scripted Speech For Multilingual Audio
Shahar Elisha, Andrew McDowell, Mariano Beguerisse-Díaz, Emmanouil Benetos
The capability of transcribing music audio into music notation is a fascinating example of human intelligence. It involves perception (analyzing complex auditory scenes), cognition (recognizing musical objects), knowledge representation (forming musical structures), and inference (testing alternative hypotheses). Automatic music transcription (AMT), i.e., the design of computational algorithms to convert acoustic music signals into some form of music notation, is a challenging task in signal processing and artificial intelligence. It comprises several subtasks, including multipitch estimation (MPE), onset and offset detection, instrument recognition, beat and rhythm tracking, interpretation of expressive timing and dynamics, and score typesetting.
Shahar Elisha, Andrew McDowell, Mariano Beguerisse-Díaz, Emmanouil Benetos
Wojciech Reise, Ximena Fernández, Maria Dominguez, Heather A. Harrington, Mariano Beguerisse-Díaz
Winstead Zhu, Md Iftekhar Tanveer, Yang Janet Liu, Seye Ojumu, Rosie Jones