scholarly journals Asymmetry in scales enhances learning of new musical structures

2021 ◽  
Vol 118 (31) ◽  
pp. e2014725118
Author(s):  
Claire Pelofi ◽  
Morwaread M. Farbood
Keyword(s):  
Substantial Impact ◽  
Musical Structures ◽  
Musical Cultures ◽  
Artificial Grammars ◽  
Finite State ◽  
Cognitive Principles ◽  
Tonal Space ◽  
Musical Systems ◽  
State Grammar ◽  
Musical Scales

Despite the remarkable variability music displays across cultures, certain recurrent musical features motivate the hypothesis that fundamental cognitive principles constrain the way music is produced. One such feature concerns the structure of musical scales. The vast majority of musical cultures use scales that are not uniformly symmetric—that is, scales that contain notes spread unevenly across the octave. Here we present evidence that the structure of musical scales has a substantial impact on how listeners learn new musical systems. Three experiments were conducted to test the hypothesis that nonuniformity facilitates the processing of melodies. Novel melodic stimuli were composed based on artificial grammars using scales with different levels of symmetry. Experiment 1 tested the acquisition of tonal hierarchies and melodic regularities on three different 12-tone equal-tempered scales using a finite-state grammar. Experiments 2 and 3 used more flexible Markov-chain grammars and were designed to generalize the effect to 14-tone and 16-tone equal-tempered scales. The results showed that performance was significantly enhanced by scale structures that specified the tonal space by providing unique intervallic relations between notes. These results suggest that the learning of novel musical systems is modulated by the symmetry of scales, which in turn may explain the prevalence of nonuniform scales across musical cultures.

scholarly journals Hierarchical and Linear Sequence Processing: An Electrophysiological Exploration of Two Different Grammar Types

2006 ◽  
Vol 18 (11) ◽  
pp. 1829-1842 ◽  
Author(s):  
Jörg Bahlmann ◽  
Thomas C. Gunter ◽  
Angela D. Friederici
Keyword(s):  
Phrase Structure ◽  
Phrase Structure Grammar ◽  
Brain Potentials ◽  
Late Positivity ◽  
Sequence Processing ◽  
Linear Sequence ◽  
Artificial Grammars ◽  
Finite State ◽  
State Grammar ◽  
Finite State Grammar

The present study investigated the processing of two types of artificial grammars by means of event-related brain potentials. Two categories of meaningless CV syllables were applied in each grammar type. The two grammars differed with regard to the type of the underlying rule. The finite-state grammar (FSG) followed the rule (AB)n, thereby generating local transitions between As and Bs (e.g., n = 2, ABAB). The phrase structure grammar (PSG) followed the rule AnBn, thereby generating center-embedded structures in which the first A and the last B embed the middle elements (e.g., n = 2, [A[AB]B]). Two sequence lengths (n = 2, n = 4) were used. Violations of the structures were introduced at different positions of the syllable sequences. Early violations were situated at the beginning of a sequence, and late violations were placed at the end of a sequence. A posteriorly distributed early negativity elicited by violations was present only in FSG. This effect was interpreted as the possible reflection of a violated local expectancy. Moreover, both grammar-type violations elicited a late positivity. This positivity varied as a function of the violation position in PSG, but not in FSG. These findings suggest that the late positivity could reflect difficulty of integration in PSG sequences.

scholarly journals Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning

2012 ◽  
Vol 367 (1598) ◽  
pp. 1984-1994 ◽  
Author(s):  
Carel ten Cate ◽  
Kazuo Okanoya
Keyword(s):  
Rule Learning ◽  
Language Faculty ◽  
Artificial Grammars ◽  
Simple Rules ◽  
Finite State ◽  
Animal Vocalizations ◽  
Phonetic Features ◽  
Species Specific ◽  
Design Experiments ◽  
State Grammar

The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple ‘rules’ like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open.

scholarly journals What the “Talking Jew’s Harp” is saying: Jew’s harp and personal song as the foundation of timbre-oriented musical systems

2019 ◽  
pp. 5-32 ◽  
Author(s):  
A. V. Nikolsky ◽  
E. E. Alekseyev ◽  
I. E. Alekxeyev ◽  
V. E. Dyakonova
Keyword(s):  
Russian Far East ◽  
Far East ◽  
Pitch Contour ◽  
Northern Eurasia ◽  
Musical Tradition ◽  
Pitch Frequency ◽  
Musical Cultures ◽  
Personal Use ◽  
Musical Systems ◽  
Musical Sounds

This article is an attempt to further develop the theory of divergence of musical systems of east and west of Eurasia by defining characteristics of a special type of musical cognition prevalent in traditional musical cultures of the indige-nous population of Siberia and Russian Far East. Its underlying trait is orientation on timbre (spectral content of musical sound) rather than pitch (frequency relations between musical sounds). Accordingly, western Eurasian musical cultures are characterized by the evolution of frequency-based modes towards Western tonality – in contrast to the northeastern Eurasian cultures’ special “timbral modes” and “spectral textures.” Unlike “tonality” of frequency-based forms of music, timbral “tonal organization” relies on personal use of music. Most known forms of musicking in timbre-based musical cultures of northern Eurasia are based on making music “for oneself” or for close circle of relatives and friends. Collective music-making here is exceedingly rare. Timbre-based music most likely has vocal roots and originates in the institution of “personal song” – a system of personal identifica-tion by means of individualized patterns of changes in rhythm, timbre and pitch contour following the model of person-alization of the speaking voice. “Personal song” allows for recognizing a person similar to the way in which we recog-nize a person by his voice. The Jew’s harp musical tradition constitutes the instrumental counterpart to personalized singing. Evolution of tonal organization of jaw harp music, largely determined by its unique acoustic features, compris-es the backbone of the historic development of timbre-based music systems.

Finite State Automata and Simple Recurrent Networks

1989 ◽  
Vol 1 (3) ◽  
pp. 372-381 ◽  
Author(s):  
Axel Cleeremans ◽  
David Servan-Schreiber ◽  
James L. McClelland
Keyword(s):  
Natural Language ◽  
Network Architecture ◽  
Intermediate Step ◽  
Recurrent Networks ◽  
Time Step ◽  
Long Distance ◽  
Finite State ◽  
Simple Recurrent Networks ◽  
State Grammar ◽  
Finite State Grammar

We explore a network architecture introduced by Elman (1988) for predicting successive elements of a sequence. The network uses the pattern of activation over a set of hidden units from time-step t−1, together with element t, to predict element t + 1. When the network is trained with strings from a particular finite-state grammar, it can learn to be a perfect finite-state recognizer for the grammar. When the network has a minimal number of hidden units, patterns on the hidden units come to correspond to the nodes of the grammar, although this correspondence is not necessary for the network to act as a perfect finite-state recognizer. We explore the conditions under which the network can carry information about distant sequential contingencies across intervening elements. Such information is maintained with relative ease if it is relevant at each intermediate step; it tends to be lost when intervening elements do not depend on it. At first glance this may suggest that such networks are not relevant to natural language, in which dependencies may span indefinite distances. However, embeddings in natural language are not completely independent of earlier information. The final simulation shows that long distance sequential contingencies can be encoded by the network even if only subtle statistical properties of embedded strings depend on the early information.

Sign in / Sign up

Export Citation Format

Share Document