Invited Research Seminar
"Multi-pitch detection and voice assignment for a cappella recordings of multiple singers"
By Rodrigo Schramm
This research focuses on a multi-pitch detection and voice assignment method applied to audio recordings containing a cappella performance with multiple singers. A novel approach combining an acoustic model for multi-pitch detection and a music language model for voice separation and assignment is proposed. The acoustic model is a spectrogram factorization process based on Probabilistic Latent Component Analysis (PLCA), driven by a 6-dimensional dictionary with pre-learned spectral templates. The voice separation component is based on hidden Markov models that use musicological assumptions. By integrating the models, the system can detect multiple concurrent pitches in vocal music and assign each detected pitch to a specific voice corresponding to a voice type such as soprano, alto, tenor or bass (SATB).
Rodrigo Schramm received his PhD in Computer Science from the Federal University of Rio Grande do Sul (UFRGS)/Brazil in 2015, where he is currently a faculty member. Between 2013 and 2014, he was visiting fellow at ICCMR - Interdisciplinary Centre for Computer Music Research - Plymouth University/UK. In 2016, he was awarded by the Royal Academy of Engineering/UK with the Newton Research Collaboration Programme Award. Currently, he is conducting research at the C4DM (QMUL) in London, focusing his activities on the development of techniques for automatic transcription of audio recordings containing multiple singers.
Host: Emilia Gómez