no code implementations • 29 Jan 2017 • Eita Nakamura, Kazuyoshi Yoshii, Shigeki Sagayama
In a recent conference paper, we have reported a rhythm transcription method based on a merged-output hidden Markov model (HMM) that explicitly describes the multiple-voice structure of polyphonic music.
1 code implementation • 24 Dec 2015 • Tomohiko Nakamura, Eita Nakamura, Shigeki Sagayama
We confirmed real-time operation of the algorithms with music scores of practical length (around 10000 notes) on a modern laptop and their tracking ability to the input performance within 0. 7 s on average after repeats/skips in clarinet performance data.
1 code implementation • 8 Apr 2014 • Eita Nakamura, Nobutaka Ono, Shigeki Sagayama, Kenji Watanabe
We study indeterminacies in realization of ornaments and how they can be incorporated in a stochastic performance model applicable for music information processing such as score-performance matching.
1 code implementation • 8 Apr 2014 • Eita Nakamura, Tomohiko Nakamura, Yasuyuki Saito, Nobutaka Ono, Shigeki Sagayama
We present a polyphonic MIDI score-following algorithm capable of following performances with arbitrary repeats and skips, based on a probabilistic model of musical performances.