57,083 research outputs found
Measuring the evolution of contemporary western popular music
Popular music is a key cultural expression that has captured listeners'
attention for ages. Many of the structural regularities underlying musical
discourse are yet to be discovered and, accordingly, their historical evolution
remains formally unknown. Here we unveil a number of patterns and metrics
characterizing the generic usage of primary musical facets such as pitch,
timbre, and loudness in contemporary western popular music. Many of these
patterns and metrics have been consistently stable for a period of more than
fifty years, thus pointing towards a great degree of conventionalism.
Nonetheless, we prove important changes or trends related to the restriction of
pitch transitions, the homogenization of the timbral palette, and the growing
loudness levels. This suggests that our perception of the new would be rooted
on these changing characteristics. Hence, an old tune could perfectly sound
novel and fashionable, provided that it consisted of common harmonic
progressions, changed the instrumentation, and increased the average loudness.Comment: Supplementary materials not included. Please see the journal
reference or contact the author
Revisiting the problem of audio-based hit song prediction using convolutional neural networks
Being able to predict whether a song can be a hit has impor- tant
applications in the music industry. Although it is true that the popularity of
a song can be greatly affected by exter- nal factors such as social and
commercial influences, to which degree audio features computed from musical
signals (whom we regard as internal factors) can predict song popularity is an
interesting research question on its own. Motivated by the recent success of
deep learning techniques, we attempt to ex- tend previous work on hit song
prediction by jointly learning the audio features and prediction models using
deep learning. Specifically, we experiment with a convolutional neural net-
work model that takes the primitive mel-spectrogram as the input for feature
learning, a more advanced JYnet model that uses an external song dataset for
supervised pre-training and auto-tagging, and the combination of these two
models. We also consider the inception model to characterize audio infor-
mation in different scales. Our experiments suggest that deep structures are
indeed more accurate than shallow structures in predicting the popularity of
either Chinese or Western Pop songs in Taiwan. We also use the tags predicted
by JYnet to gain insights into the result of different models.Comment: To appear in the proceedings of 2017 IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP
ALEA III, Millennium Project 1950 - 1960, March 23, 1996
This is the concert program of the ALEA III, Millennium Project 1950 - 1960 performance on Saturday, March 23, 1996 at 8:00 p.m., at the Tsai Performance Center, 685 Commonwealth Avenue, Boston, Massachusetts. Works performed were Zyklus by Karlheinz Stockhausen, Serenata by Goffredo Petrassi, Psalms by Lukas Foss, 6 Etudes by Yannis Constantinides, Quintette Instrumental by Heitor Villa-Lobos, and Oiseaux Exotiques by Olivier Messiaen. Digitization for Boston University Concert Programs was supported by the Boston University Humanities Library Endowed Fund
A computational framework for aesthetical navigation in musical search space
Paper presented at 3rd AISB symposium on computational creativity, AISB 2016, 4-6th April, Sheffield. Abstract. This article addresses aspects of an ongoing project in the generation of artificial Persian (-like) music. Liquid Persian Music software (LPM) is a cellular automata based audio generator. In this paper LPM is discussed from the view point of future potentials of algorithmic composition and creativity. Liquid Persian Music is a creative tool, enabling exploration of emergent audio through new dimensions of music composition. Various configurations of the system produce different voices which resemble musical motives in many respects. Aesthetical measurements are determined by Zipf’s law in an evolutionary environment. Arranging these voices together for producing a musical corpus can be considered as a search problem in the LPM outputs space of musical possibilities. On this account, the issues toward defining the search space for LPM is studied throughout this paper
Instrumentational complexity of music genres and why simplicity sells
Listening habits are strongly influenced by two opposing aspects, the desire
for variety and the demand for uniformity in music. In this work we quantify
these two notions in terms of musical instrumentation and production
technologies that are typically involved in crafting popular music. We assign a
"complexity value" to each music style. A style is complex if it shows the
property of having both high variety and low uniformity in instrumentation. We
find a strong inverse relation between variety and uniformity of music styles
that is remarkably stable over the last half century. Individual styles,
however, show dramatic changes in their "complexity" during that period. Styles
like "new wave" or "disco" quickly climbed towards higher complexity in the 70s
and fell back to low complexity levels shortly afterwards, whereas styles like
"folk rock" remained at constant high complexity levels. We show that changes
in the complexity of a style are related to its number of sales and to the
number of artists contributing to that style. As a style attracts a growing
number of artists, its instrumentational variety usually increases. At the same
time the instrumentational uniformity of a style decreases, i.e. a unique
stylistic and increasingly complex expression pattern emerges. In contrast,
album sales of a given style typically increase with decreasing complexity.
This can be interpreted as music becoming increasingly formulaic once
commercial or mainstream success sets in.Comment: 17 pages, 5 figures, Supporting Informatio
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