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Stefan Lattner

Assistant Researcher

music

We are usually unaware of the enormous computing power needed by our brain when listening to music. When trying to make sense of music, we constantly have to classify, sort, remember, structure, and connect a vast number of musical events. Moreover, these events do not only consist of notes, chords, and rhythms but are also characterized by “colors of sound.” These ever-changing frequencies, resulting in complex soundscapes, are at the heart of our musical experiences. I use computer models to simulate the cognitive processes involved when listening to music, to create better tools for music production and music analysis. Creating compositions, musical arrangements, and unique sounds using machine learning and artificial intelligence will lead to a streamlined music production workflow and to entirely different ways to engage with music as a whole.

2018

Audio to score alignment using transposition invariant features

Topics:
music
Authors
Arzt Andreas, Stefan Lattner,

19th International Society for Music Information Retrieval Conference (ISMIR), 2018.

2018

A predictive model for music-based on learned interval representations

Topics:
music
Authors
Stefan Lattner, Grachten Maarten, Widmer Gerhard,

19th International Society for Music Information Retrieval Conference (ISMIR), 2018.

2018

Learning interval representations from polyphonic music sequences

Topics:
music
Authors
Stefan Lattner, Grachten Maarten, Widmer Gerhard,

19th International Society for Music Information Retrieval Conference (ISMIR), 2018.