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Statistical Learning of Harmonic Movement

Dan Ponsford, Geraint Wiggins, Chris Mellish
1999 Journal of New Music Research  
The corpus is preprocessed in a novel way, automatically converting the harmonies into a normal form to capture the underlying harmonic similarities between pieces.  ...  A probabilistic method is used to capture and generalise from the local harmonic movement of a corpus of seventeenth-century dance music.  ...  Hidden Markov models The following definition of a hidden Markov model (HMM) is from Church and Mercer (1993) .  ... 
doi:10.1076/jnmr. fatcat:tcotmz5i4bdrnlqgbos2jsmknq

DeepBach: a Steerable Model for Bach Chorales Generation [article]

Gaëtan Hadjeres and François Pachet and Frank Nielsen
2017 arXiv   pre-print
This paper introduces DeepBach, a graphical model aimed at modeling polyphonic music and specifically hymn-like pieces.  ...  Our model is also steerable in the sense that a user can constrain the generation by imposing positional constraints such as notes, rhythms or cadences in the generated score.  ...  It is an integer between 1 and 4: there is no distinction between beats in a bar so that our model is able to deal with chorales with three and four beats per measure.  ... 
arXiv:1612.01010v2 fatcat:e6otgvgx25dmvhaekupb7fhigu

Deep Learning-Based Automatic Downbeat Tracking: A Brief Review [article]

Bijue Jia, Jiancheng Lv, Dayiheng Liu
2019 arXiv   pre-print
Previous researches either focus on feature engineering (extracting certain features by signal processing, which are semi-automatic solutions); or have some limitations: they can only model music audio  ...  Despite significant research efforts, downbeat tracking still remains a challenge.  ...  Hidden Markov Model Hidden Markov Model (HMM) is a probability model with respect to time series.  ... 
arXiv:1906.03870v1 fatcat:torfkkzd6jfr3pxa5oku4k3e6i

BREVE: An HMPerceptron-Based Chord Recognition System [chapter]

Daniele P. Radicioni, Roberto Esposito
2010 Studies in Computational Intelligence  
Tonal harmony analysis is a sophisticated task.  ...  The solution proposed to the problem relies on a conditional model, where domain knowledge is encoded in the form of Boolean features.  ...  Raphael & Stoddard [24] proposed a machine learning approach based on a Hidden Markov Model that computes Roman numeral analysis (that is, the higher level, functional analysis mentioned above).  ... 
doi:10.1007/978-3-642-11674-2_7 fatcat:dm4h3mkenjdejgxqahdh4i5iii

Combining Harmony-Based And Novelty-Based Approaches For Structural Segmentation

Johan Pauwels, Florian Kaiser, Geoffroy Peeters
2013 Zenodo  
Recently however, this approach has been extended to also include contrast between a homogeneous and a non-homogeneous section [6] .  ...  Additionally, the combined system is also less sensitive to the choice of relative chord models than the harmony-based method is.  ... 
doi:10.5281/zenodo.1416104 fatcat:u5rffiozhbcglp4v4olunsqyli

Improving Music Genre Classification Using Automatically Induced Harmony Rules

Amélie Anglade, Emmanouil Benetos, Matthias Mauch, Simon Dixon
2010 Journal of New Music Research  
We present a new genre classification framework using both low-level signal-based features and high-level harmony features.  ...  A state of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences.  ...  Acknowledgements This work was done while the third author was a Research Student at Queen Mary, University of London.  ... 
doi:10.1080/09298215.2010.525654 fatcat:hu7w3o5udnca5ems4ytjt7w7ki

A Functional Taxonomy of Music Generation Systems

Dorien Herremans, Ching-Hua Chuan, Elaine Chew
2017 ACM Computing Surveys  
This design-centered approach contrasts with predominant methods-based surveys and facilitates the identification of grand challenges to set the stage for new breakthroughs.  ...  We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed.  ...  At each point, a decision is made, based on a second-order Markov model, to invert melodic fragments based on the chord, or to copy the previous one.  ... 
doi:10.1145/3108242 fatcat:wcp2p3mu4fgndclqrwlcwzkyoa

Automatic Detection of Hierarchical Structure and Influence of Structure on Melody, Harmony and Rhythm in Popular Music

Shuqi Dai, Huan Zhang, Roger Dannenberg
2020 Zenodo  
Repetition is a basic indicator of musical structure. This study introduces new algorithms for identifying musical phrases based on repetition.  ...  Phrases combine to form sections yielding a two-level hierarchical structure.  ...  We introduced a new hierarchical structure analysis algorithm. With it, we analyzed harmony, melody and rhythm in the context of multi-level structure.  ... 
doi:10.5281/zenodo.4285402 fatcat:sv7fww6zn5cpjaqxsihapcdpkm

Automatic Analysis and Influence of Hierarchical Structure on Melody, Rhythm and Harmony in Popular Music [article]

Shuqi Dai and Huan Zhang and Roger B. Dannenberg
2020 arXiv   pre-print
Repetition is a basic indicator of musical structure. This study introduces new algorithms for identifying musical phrases based on repetition.  ...  Phrases combine to form sections yielding a two-level hierarchical structure.  ...  We introduced a new hierarchical structure analysis algorithm. With it, we analyzed harmony, melody and rhythm in the context of multi-level structure.  ... 
arXiv:2010.07518v1 fatcat:sqou3t6mw5hp3kw3zq6kqacnqu

A Regularity-Constrained Viterbi Algorithm And Its Application To The Structural Segmentation Of Songs

Gabriel Sargent, Frédéric Bimbot, Emmanuel Vincent
2011 Zenodo  
of similar states in Hidden Markov Models (HMMs) [11] .  ...  The automatic structural segmentation of songs is generally addressed by analyzing the homogeneity and the repetitiveness of the musical content over time (timbre, harmony, rhythm, melody).  ... 
doi:10.5281/zenodo.1415949 fatcat:6nylrxye6vafpahwyogpfletoq

Automatic Harmony Analysis Of Jazz Audio Recordings

Vsevolod Eremenko, Xavier Serra, Baris Bozkurt
2018 Zenodo  
Then we evaluate some existing state of the art algorithms and develop our own using beat detection, chroma features extraction, and probabilistic model as building blocks.  ...  Also, we suggest a novel way of visualizing chroma distribution based on Compositional Data Analysis techniques.  ...  For a more in-depth introduction to probability, Gaussian Mixture Models, Hidden Markov Models and Conditional Random Fields one could check corresponding chapters of Murphy textbook [46] .  ... 
doi:10.5281/zenodo.1467949 fatcat:pwy5xag4nzc4parkjbfbm33bta

Functional Harmonic Analysis Using Probabilistic Models

Christopher Raphael, Joshua Stoddard
2004 Computer Music Journal  
The analysis is performed with a hidden Markov model and, as such, is automatically trainable from generic MIDI files and capable of finding the globally optimal harmonic labeling.  ...  An extension to a more complex probabilistic graphical model is outlined in which music is modeled as a collection of voices that evolve independently given the harmonic progression.  ...  We model this sequence probabilistically as a homogeneous Markov chain r $ &s t! u v w s x ¨ s t! ) y¡ r $ es t! ¨u w s t!  ... 
doi:10.1162/0148926041790676 fatcat:qwdomcqpijdqbebfqqkszlgeju

Artificial Musical Intelligence: A Survey [article]

Elad Liebman, Peter Stone
2020 arXiv   pre-print
its pursuit, with a particular emphasis on machine learning methods.  ...  This article provides a definition of musical intelligence, introduces a taxonomy of its constituent components, and surveys the wide range of AI methods that can be, and have been, brought to bear in  ...  Abdallah et al. propose a Bayesian approach to clustering segments based on harmony, rhythm, pitch and timbre.  ... 
arXiv:2006.10553v1 fatcat:2j6i27wrsfawpgcr2unxdgngd4

A geometrical distance measure for determining the similarity of musical harmony

W. Bas de Haas, Frans Wiering, Remco C. Veltkamp
2013 International Journal of Multimedia Information Retrieval  
The distance function we present, the Tonal pitch step distance, is based on a cognitive model of tonality and captures the change of harmonic distance to the tonal center over time.  ...  Furthermore, we demonstrate in a case study how our harmonic similarity measure can contribute to the musicological discussion of the melody and harmony in large-scale corpora.  ...  The authors use a Markov model to model the transition distributions between these vectors for every piece.  ... 
doi:10.1007/s13735-013-0036-6 fatcat:dbypj66bazgsdo26qls5xywpqq

A Conditional Random Field Framework for Robust and Scalable Audio-to-Score Matching

Cyril Joder, Slim Essid, Gaël Richard
2011 IEEE Transactions on Audio, Speech, and Language Processing  
This strategy reduces the complexity, yielding a better overall efficiency than the classic beam search method used in HMM-based models.  ...  Three types of features are used, characterizing the local harmony, note attacks and tempo.  ...  The use of averaged observations is musically justified since the harmony (and thus the chroma information) is in general homogeneous over a whole beat (or measure) duration.  ... 
doi:10.1109/tasl.2011.2134092 fatcat:2h5x5adnbzhahbc72so2adjf2m
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