Name
Title | ||
|---|---|---|
Tempo Driven Audio-to-Score Alignment Using Spectral Decomposition and Online Dynamic Time Warping. |
Abstract | ||
|---|---|---|
In this article, we present an online score following framework designed to deal with automatic accompaniment. The proposed framework is based on spectral factorization and online Dynamic Time Warping (DTW) and has two separated stages: preprocessing and alignment. In the first one, we convert the score into a reference audio signal using a MIDI synthesizer software and we analyze the provided information in order to obtain the spectral patterns (i.e., basis functions) associated to each score unit. In this work, a score unit represents the occurrence of concurrent or isolated notes in the score. These spectral patterns are learned from the synthetic MIDI signal using a method based on Non-negative Matrix Factorization (NMF) with Beta-divergence, where the gains are initialized as the ground-truth transcription inferred from the MIDI. On the second stage, a non-iterative signal decomposition method with fixed spectral patterns per score unit is used over the magnitude spectrogram of the input signal resulting in a distortion matrix that can be interpreted as the cost of the matching for each score unit at each frame. Finally, the relation between the performance and the musical score times is obtained using a strategy based on online DTW, where the optimal path is biased by the speed of interpretation. Our system has been evaluated and compared to other systems, yielding reliable results and performance. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/2926717 | ACM TIST |
Keywords | Field | DocType |
Accompaniment,audio-to-score alignment,score following,online algorithm,non-negative matrix factorization (NMF),beta-divergence,dynamic time warping (DTW),speed of interpretation,tempo | Audio signal,Pattern recognition,Dynamic time warping,Spectrogram,Computer science,Matrix decomposition,MIDI,Score following,Non-negative matrix factorization,Artificial intelligence,Machine learning,Spectral theorem | Journal |
Volume | Issue | ISSN |
8 | 2 | 2157-6904 |
Citations | PageRank | References |
4 | 0.43 | 25 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| f j rodriguezserrano | 1 | 13 | 1.70 |
| J.J. Carabias | 2 | 12 | 3.36 |
| Pedro Vera-Candeas | 3 | 59 | 8.32 |
| Martinez-Munoz, D. | 4 | 26 | 4.31 |