TECHNOLOGIES IN SoloLa!
SoloLa! applies a number of music signal processing and machine learning algorithms to achieve our goal — transcribing lead guitar in mixed recording into sheet music with just a click of the mouse. The figure shows the workflow of SoloLa!. The audio signal of lead guitar is isolated from the music mixture by the process of Monaural source separation. For the isolated lead guitar audio signal, Melody extraction aims at automatically estimating the fundamental frequency corresponding to the pitch of the lead guitar to generate a series of consecutive pitch values which are continuous in both time and frequency, a.k.a. melody contour. Expression style recognition refers to the detection of applied lead guitar playing techniques such as string bend, slide or vibrato. Note tracking is the task of recognizing the note event from the estimated frame-level melody contour estimated in the melody extraction stage. The purpose of the task is to transform the mid-level melody contour into high-level symbolic notation. Finally, Automatic fingering arrangement maps the sequence of notes to a set of guitar fretboard positions.
MAIN REFERENCES
Zafar Rafii and Bryan Pardo. "REpeating Pattern Extraction Technique (REPET): A Simple Method for Music/Voice Separation," IEEE Transactions on Audio, Speech, and Language Processing, 21(1):71--82, January 2013.
Derry FitzGerald, "Harmonic/Percussive Separation using Median Filtering", in Proc. of the International Conference on Digital Audio Effects (DAFx), 2010.
J. Salamon and E. Gómez. "Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics", IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, Aug. 2012.
Gregory Burlet and Ichiro Fujinaga, "Robotaba Guitar Tablature Transcription Framework", in Proc. of the 14th International Society for Music Information Retrieval Conference (ISMIR), 2013.
M. Mauch and S. Dixon. "pYIN: A Fundamental Frequency Estimator Using Probabilistic Threshold Distributions", in Proc. of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014), 2014.
L. Su, L.-F. Yu and Y.-H. Yang. "Sparse Cepstral and Phase Codes for Guitar Playing Technique Classification", in Proc. of the 15th International Society for Music Information Retrieval Conference (ISMIR), 2014.
Y.-P. Chen, L. Su and Y.-H. Yang. "Electric Guitar Playing Technique Detection in Real-World Recording Based on F0 Sequence Pattern Recognition", in Proc. of the 16th International Society for Music Information Retrieval Conference (ISMIR), 2015.
J. Driedger and M. Müller. "TSM Toolbox: MATLAB Implementations of Time-Scale Modification Algorithms", in Proc. of the International Conference on Digital Audio Effects (DAFx), 2014.
B. McFee, E. Humphrey, and J.P. Bello, "A software framework for musical data augmentation", in Proc. of the 16th International Society for Music Information Retrieval Conference (ISMIR), 2015.
Sebastian Böck, Florian Krebs and Gerhard Widmer, "Accurate Tempo Estimation based on Recurrent Neural Networks and Resonating Comb Filters", in Proc. of the 16th International Society for Music Information Retrieval Conference (ISMIR), 2015.
APPLIED LIBRARIES FOR MUSIC SIGNAL ANALYSIS & MACHINE LEARNING