133 research outputs found
Implicit learning of recursive context-free grammars
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning
experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have
not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing
features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured
the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both
distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes
even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between
individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for
tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex
context-free structures, which model some features of natural languages. They support the relevance of artificial grammar
learning for probing mechanisms of language learning and challenge existing theories and computational models of
implicit learning
Comments on "Facilitation and Coherence Between the Dynamic and Retrospective Perception of Segmentation in Computer-Generated Music," by Freya Bailes and Roger T. Dean
Although the study by Bailes & Dean (2007) addresses an underresearched
area of auditory and musical perception, it raises questions concerning
stimuli, methodology, and the study's relation to previous research, that are outlined in
this commentary
A statistical MMN reflects the magnitude of transitional probabilities in auditory sequences
Within the framework of statistical learning, many behavioural studies
investigated the processing of unpredicted events. However, surprisingly few
neurophysiological studies are available on this topic, and no statistical
learning experiment has investigated electroencephalographic (EEG) correlates
of processing events with different transition probabilities. We carried out
an EEG study with a novel variant of the established statistical learning
paradigm. Timbres were presented in isochronous sequences of triplets. The
first two sounds of all triplets were equiprobable, while the third sound
occurred with either low (10%), intermediate (30%), or high (60%) probability.
Thus, the occurrence probability of the third item of each triplet (given the
first two items) was varied. Compared to high-probability triplet endings,
endings with low and intermediate probability elicited an early anterior
negativity that had an onset around 100âms and was maximal at around 180âms.
This effect was larger for events with low than for events with intermediate
probability. Our results reveal that, when predictions are based on
statistical learning, events that do not match a prediction evoke an early
anterior negativity, with the amplitude of this mismatch response being
inversely related to the probability of such events. Thus, we report a
statistical mismatch negativity (sMMN) that reflects statistical learning of
transitional probability distributions that go beyond auditory sensory memory
capabilities
A semi-automated workflow paradigm for the distributed creation and curation of expert annotations
The creation and curation of labeled datasets can be an arduous, expensive, and time-consuming task. We introduce a workflow paradigm for remote consensus-building between expert annotators, while considerably reducing the associated administrative overhead through automation. Most music annotation tasks rely heavily on human interpretation and therefore defy the concept of an objective and indisputable ground truth. Thus, our paradigm invites and documents inter-annotator controversy based on a transparent set of analytical criteria, and aims at putting forth the consensual solutions emerging from such deliberations. The workflow that we suggest traces the entire genesis of annotation data, including the relevant discussions between annotators, reviewers, and curators. It adopts a well-proven pattern from collaborative software development, namely distributed version control, and allows for the automation of repetitive maintenance tasks, such as validity checks, message dispatch, or updates of meta- and paradata. To demonstrate the workflow's effectiveness, we introduce one possible implementation through GitHub Actions and showcase its success in creating cadence, phrase, and harmony annotations for a corpus of 36 trio sonatas by Arcangelo Corelli. Both code and annotated scores are freely available and the implementation can be readily used in and adapted for other MIR projects
Wie wissenschaftlich muss Musiktheorie sein?. Chancen und Herausforderungen musikalischer Korpusforschung
Korpusbasierte Forschung nimmt in der Sprach- und Literaturwissenschaft schon seit Langem einen wichtigen Platz ein. In der Musikforschung dagegen gewann sie erst vor Kurzem an Bedeutung. Die GrĂŒnde fĂŒr diese verspĂ€tete Akzeptanz sind vielfĂ€ltig und mitunter einer tiefgreifenden Skepsis gegenĂŒber der Anwendung statistisch-quantitativer Methoden auf Musik als Kunstobjekt geschuldet. Der vorliegende Beitrag motiviert musikalische Korpusforschung, indem er grundsĂ€tzliche Probleme herkömmlicher Repertoireforschung (intuitive Statistik, methodische Intransparenz, Urteilsheuristiken) und gegenwĂ€rtiger Korpusforschung (z.B. Stichprobenerhebung, mangelnde Korpora und Annotationsstandards) aufzeigt und anhand reprĂ€sentativer Studien in den Bereichen Harmonik, Kontrapunktik, Melodiebildung und Rhythmik/Metrik exemplarisch diskutiert. Der Beitrag schlieĂt mit einem PlĂ€doyer fĂŒr die Einbeziehung quantitativer AnsĂ€tze in der Musiktheorie im Rahmen eines ĂŒbergeordneten âșMixed Methodsâč-Paradigmas.
Corpus-based research has long been occupying a prominent position in literary studies and linguistics. In musicology, by contrast, it is about to gain in importance only fairly recently. The reasons for this delayed acceptance are manifold. Among other things, they are rooted in a deep skepticism toward applying statistical-quantitative methods to music as an object of art. This article supports musicological corpus research by pointing out general problems inherent to traditional repertoire research (intuitive statistics, methodological non-transparency, and heuristics in judgment) as well as current corpus research (e.g., biased sampling, paucity of corpora, and lack of annotation standards). These problems are discussed in reference to prominent studies in the domains of harmony, counterpoint, melody, and rhythm/meter. The article concludes by making a case for the integration of quantitative approaches in music theory into the overarching framework of a âșmixed methodsâč paradigm
The diachronic development of Debussyâs musical style: a corpus study with Discrete Fourier Transform
Claude Debussyâs personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretability of Discrete Fourier Transforms over pitch-class distributions, we performed a corpus study over Debussyâs solo-piano works in order to investigate the diachronic development of such stylistic features across the composerâs lifespan. We propose quantitative heuristics for the prevalence of different pitch-class prototypes, the fragmentation of a piece across different prototypes, as well as some aspect of the overall coherence of a piece. We found strong evidence for a decrease of diatonicity in favour of octatonicity, as well as for an increase of fragmentation accompanied by non-decreasing coherence. These results contribute to the understanding of the historical development of extended-tonal harmony, while representing a fertile testing ground for the interaction of computational corpus-based methods with traditional music analytical approaches
Western listeners detect boundary hierarchy in Indian music: a segmentation study
How are listeners able to follow and enjoy complex pieces of music? Several theoretical frameworks suggest links between the process of listening and the formal structure of music, involving a division of the musical surface into structural units at multiple hierarchical levels. Whether boundaries between structural units are perceivable to listeners unfamiliar with the style, and are identified congruently between naĂŻve listeners and experts, remains unclear. Here, we focused on the case of Indian music, and asked 65 Western listeners (of mixed levels of musical training; most unfamiliar with Indian music) to intuitively segment into phrases a recording of sitar ÄlÄp of two different rÄga-modes. Each recording was also segmented by two experts, who identified boundary regions at section and phrase levels. Participant- and region-wise scores were computed on the basis of "clicks" inside or outside boundary regions (hits/false alarms), inserted earlier or later within those regions (high/low "promptness"). We found substantial agreementâexpressed as hit rates and click densitiesâamong participants, and between participantsâ and expertsâ segmentations. The agreement and promptness scores differed between participants, levels, and recordings. We found no effect of musical training, but detected real-time awareness of grouping completion and boundary hierarchy. The findings may potentially be explained by underlying general bottom-up processes, implicit learning of structural relationships, cross-cultural musical similarities, or universal cognitive capacitie
Towards a Unified Model of Chords in Western Harmony
Chord-based harmony is an important aspect of many types of Western music, across genres, regions, and historical eras. However, the consistent representation and comparison of harmony across a wide range of styles (e.g., classical music, Jazz, Rock, or Pop) is a challenging task. Moreover, even within a single musical style, multiple theories of harmony exist, each relying on its own (possibly implicit) assumptions and leading to harmonic analyses with a distinct focus (e.g., on the root of a chord vs. its bass note) or representation (e.g., spelled vs. enharmonic pitch classes). Cross-stylistic and cross-theory comparisons are therefore even more difficult, particularly in a large-scale computational setting that requires a common overarching representation. To address these problems, we propose a model which allows for the representation of chords at multiple levels of abstraction: from chord realizations on the score level (if available), to pitch-class collections (including a potential application of different equivalences, such as enharmonic or octave equivalence), to pitch- and chord-level functions and higher-order abstractions. Importantly, our proposed model is also well-defined for theories which do not specify information at each level of abstraction (e.g., some theories make no claims about harmonic function), representing only those harmonic properties that are explicitly included and inducing others where possible (e.g., deriving scale degrees from root and key information). Our model thus represents an important step towards a unified representation of harmony and its various applications.This research was supported by the Swiss National Science Foundation within the project âDistant Listening â The Development of Harmony over Three Centuries (1700â2000)â (Grant no. 182811). This project is being conducted at the Latour Chair in Digital and Cognitive Musicology, generously funded by Mr. Claude Latour
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