Music Segments Research Articles

Perceiving Boundaries in Unfamiliar Turkish Makam Music

Music segmentation is a widely researched topic within music perception. Even though there is extensive data on the role of surface structure features and music training (e.g., Deliège, 1987) in segmentation, not much is known yet about the influence of implicit knowledge-based features acquired through musical enculturation. The goal of our study was to fill this gap. Makam music-trained musicians, nonmusicians, and Western listeners marked their segmentations online as they listened to mostly 19th century, unfamiliar Turkish makam tunes, all recorded in a Qānūn timbre on MIDI with retained microtonal structure. In addition, two experts segmented the tunes in a free-time setting. We found considerable within- and across-group agreement, as well as good agreement with the expert segmentations. After transforming each participant’s segmentations into “hits” and “false alarms” based on their match or mismatch with expert segmentations, we observed that musicians overlapped significantly more with expert segmentations than do the other two groups. Segmentations in all three groups were strongly driven by mostly local surface features. Overall, our results are more supportive of a universality claim as proposed by the Gestalt school of psychology than an enculturation claim.

German Music Libraries in the Age of Digital Transformation—Challenges and Perspectives

German Music Libraries in the Age of Digital Transformation—Challenges and Perspectives Verena Funtenberger (bio) The processes of change in the digital society and their consequences for libraries affect also music libraries, even more they seem bundled herein as under a magnifying glass. Attractive new buildings and facilities of recent years such as in Stuttgart, Essen, Nuremberg, Wiesbaden or currently in Detmold cannot hide the fact that this branch of librarianship is facing major challenges. Here too, as the number of loans of physical media decreases, new concepts must be developed and new paths explored. Digital Offerings in Music Libraries Music libraries have already arrived in the digital age. They collect and make accessible not only sheet music, music books and recording media, they digitise their own collections and provide their customers with electronic resources and services available in digital libraries or an institution’s repositories. These are either accessible on the Web free of charge or licensed, meaning access is possible only via the library’s network or by individual subscription. The most extensive digitised music collections can be found in large academic libraries. They are merged in the Virtual Library of Musicology, which will be presented in the next section. Like the majority of library customers, the user interested in music prefers media and information—if possible—in electronic form on a PC, tablet, or smartphone and available at any time and any location. Until now, public libraries have been able to only partially satisfy these requirements. The legal framework for the lending of e-books have not been clarified and the publishers have not been obligated to grant licenses. Meanwhile, the digital German lending platform “Onleihe”, provided in the majority of public libraries offers more music books in electronic format, especially music education titles, biographies of musicians, and introductory literature on musical topics. The deficiency of legal rules and the rigid austerity policy of the states and municipalities have prevented acknowledgment of the changed user behavior. Both conservatory libraries as well as public music libraries lack sufficient funds and technical equipment for database licenses and for the installation of network access. In municipal music libraries the fee-based digital content hardly exceeds the music segments of the established German Web portal Munzinger (https://www.munzinger.de/, accessed 16 December 2016). But even the included remote access to the Naxos Music Libraries—“Classical Music” and “Jazz”—which provides over 100,000 compact disc recordings through streaming technology in high quality sound and with introductions to musical works, cannot be offered in all music libraries. Nothing less than privileged are the customers of the Hamburg Bücherhallen and the City Library of Hannover. They are the first German library [End Page 86] users having access to over nine million songs from all genres from over 28,000 labels and over 15,000 music videos via the American streaming service Freegal Music (http://www.freegalmusic.com/, accessed 16 December 2016). They are even allowed to download three tracks per week. Of course, this offer has its price, and that cost might currently not be within most libraries’ reach. Sheet music collections are also innovating. The International Music Score Library Project, IMSLP (http://imslp.org/, accessed 16 December 2016), or Petrucci Music Library for short, the world’s largest online collection of public domain and freely available scores, has turned into a true competitor for music publishers, music shops, and music libraries. The argument that the partial, badly scanned scores were no serious alternatives to carefully prepared critical score editions seem relevant only for professional musicians and scholars. A small indication may be the response of a music teacher whose student had printed out a Haydn sonata from the Petrucci Music Library. Asked why he did not suggest that he use a critical edition, he commented tersely: “I’m happy if he still plays Haydn at all!” The gaps in the contents of the Petrucci Music Library, for example, contemporary and popular music are filled by large commercial download sheet music platforms like Notafina (https://en.notafina.de/) or Sheet Music Plus (http://www.sheetmusicplus.com/, both accessed 16 December 2016). Licensing models for libraries have not become an issue, because...

Information Distribution Within Musical Segments

In research on word recognition, it has been shown that word beginnings have higher information content for word identification than word endings; this asymmetric information distribution within words has been argued to be due to the communicative pressure to allow words in speech to be recognized as early as possible. Through entropy analysis using two representative datasets from Wikifonia and the Essen folksong corpus, we show that musical segments also have higher information content (i.e., higher entropy) in segment beginnings than endings. Nevertheless, this asymmetry was not as dramatic as that found within words, and the highest information content was observed in the middle of the segments (i.e., an inverted U pattern). This effect may be because the first and last notes of a musical segment tend to be tonally stable, with more flexibility in the first note for providing the initial context. The asymmetric information distribution within words has been shown to be an important factor accounting for various asymmetric effects in word reading, such as the left-biased preferred viewing location and optimal viewing position effects. Similarly, the asymmetric information distribution within musical segments is a potential factor that can modulate music reading behavior and should not be overlooked.

Multi-scale Modelling of Segmentation

While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects of experimental task (i.e., real-time vs. annotated segmentation), nor of musicianship on boundary perception are clear. Our study assesses musicianship effects and differences between segmentation tasks. We conducted a real-time experiment to collect segmentations by musicians and nonmusicians from nine musical pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary indication density, although this might be contingent on stimuli and other factors. In line with other studies, no musicianship effects were found: our results showed high agreement between groups and similar inter-subject correlations. Also consistent with previous work, time scales between one and two seconds were optimal for combining boundary indications. In addition, we found effects of task on number of indications, and a time lag between tasks dependent on beat length. Also, the optimal time scale for combining responses increased when the pulse clarity or event density decreased. Implications for future segmentation studies are raised concerning the selection of time scales for modelling boundary density, and time alignment between models.

Modeling Perceptions of Valence in Diverse Music

We investigate the roles of the acoustic parameters intensity and spectral flatness in the modeling of continuously measured perceptions of affect in nine diverse musical extracts. The extract sources range from Australian Aboriginal and Balinese music, to classical music from Mozart to minimalism and Xenakis; and include jazz, ambient, drum n' bass and performance text. We particularly assess whether modeling perceptions of the valence expressed by the music, generally modeled less well than the affective dimension of arousal, can be enhanced by inclusion of perceptions of change in the sound, human agency, musical segmentation, and random effects across participants, as model components. We confirm each of these expectations, and provide indications that perceived change in the music may eventually be subsumed adequately under its components such as acoustic features and agency. We find that participants vary substantially in the predictors useful for modeling their responses (judged by the random effects components of mixed effects cross-sectional time series analyses). But we also find that pieces do too, while yet sharing sufficient features that a single common model of the responses to all nine pieces has competitive precision.

Impact of Noise Reduction Algorithm in Cochlear Implant Processing on Music Enjoyment.

Noise reduction algorithm (NRA) in speech processing strategy has positive impact on speech perception among cochlear implant (CI) listeners. We sought to evaluate the effect of NRA on music enjoyment. Prospective analysis of music enjoyment. Academic medical center. Normal-hearing (NH) adults (N = 16) and CI listeners (N = 9). Subjective rating of music excerpts. NH and CI listeners evaluated country music piece on three enjoyment modalities: pleasantness, musicality, and naturalness. Participants listened to the original version and 20 modified, less complex versions created by including subsets of musical instruments from the original song. NH participants listened to the segments through CI simulation and CI listeners listened to the segments with their usual speech processing strategy, with and without NRA. Decreasing the number of instruments was significantly associated with increase in the pleasantness and naturalness in both NH and CI subjects (p < 0.05). However, there was no difference in music enjoyment with or without NRA for either NH listeners with CI simulation or CI listeners across all three modalities of pleasantness, musicality, and naturalness (p > 0.05): this was true for the original and the modified music segments with one to three instruments (p > 0.05). NRA does not affect music enjoyment in CI listener or NH individual with CI simulation. This suggests that strategies to enhance speech processing will not necessarily have a positive impact on music enjoyment. However, reducing the complexity of music shows promise in enhancing music enjoyment and should be further explored.

The Sounds and Moves of ibtiẓāl in 20th-Century Iran

The scene opens with the camera zooming in on a small raised stage where a group of muṭribs (minstrel performers) are enacting a rūḥawzī piece. At stage left, a young man is singing a love song that describes the physical features of his beloved, Chihilgis. He is accompanied by an ensemble that plays rhythmic music (in 6/8 meter) on traditional Iranian instruments—the tunbak, the tār, and the kamānchih. Standing next to the singer is Chihilgis, performed by a crossed-dressed performer (zanpūsh) who sports a long wig and moves flirtatiously to the song, making coquettish gestures with the eyes, lips, and shoulders. Chihilgis then joins the dance center stage with the two other main characters: the protagonist, enacted by the black-faced performer Mubarak, who has a tambourine (dāyirih) in hand; and Haji, Chihilgis’ old father, who sports a white cotton beard. With variations based on the characters, the dance consists of typical muṭribī moves, including exaggerated wrist and hip rotations, facial gestures such as blinking, and sliding head movements. This musical segment is followed by a witty, humorous dialogue between Mubarak and Haji with sexual undertones.

A Study on Feature Selection and Classification Techniques of Indian Music

In this paper we present the effect of four feature selection algorithms namely genetic algorithm, Forward feature selection, information gain and correlation based on four different classifiers (Decision tree C4.5, K-Nearest neighbors, neural network and support vector machine). The feature sets used in this paper are extracted features from the preprocessed songs using MIR Toolbox in MATLAB, which encompass rhythm based, timbre based, pitch based, tonality based and dynamic features. Feature vectors are extracted from music segments from first 30 seconds and last thirty seconds of the music signal (time-decomposition). Experiments were carried out on the three dominant genres of Indian music: Carnatic, Hindustani and Bollywood. Our dataset is small with 290 songs, trimmed to extract the first and the last 30 second percepts. As pure Carnatic and Hindustani music being more prevalent in traditional settings, have limited work done to make their digital copies available but the collection of music we have used consists of songs of some of the most profound singers contributing to each of these genres. For high-dimensional feature sets, the feature selection provides a compact but discriminative feature subset which has an interesting trade-off between classification accuracy and computational effort. The experimental results have shown that the common features selected by each of the feature selection algorithms with respect to classifiers and percentage of classification accuracies for all the classification algorithms. Furthermore, it can be observed from our experiment that information gain based feature selection gives better and consistent accuracies than other feature selection algorithms and Neural network and SVM classifiers are the best suited classifiers for Indian Song dataset.

Probabilistic Segmentation of Folk Music Recordings

The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.

PyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis.

Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library.

System &amp; Contrast

This article introduces the System &amp;Contrast (S&amp;C) model, which aims at describing the inner organization of structural segments within music pieces as: (i) a carrier system, i.e., a sequence of morphological elements forming a network of self-deducible syntagmatic relationships, and (ii) a contrast, i.e., a substitutive element, usually the last one, which departs from the logic implied by the carrier system. Initially used for the structural annotation of pop songs (Bimbot, Deruty, Sargent, &amp; Vincent, 2012), the S&amp;C model provides a framework to describe implication patterns in musical segments by encoding similarities and relations between its elements. It is applicable at several timescales to various musical dimensions in a polymorphous way, thus offering an attractive meta-description of musical contents. We formalize the S&amp;C model, illustrate how it applies to music and establish its filiation with Narmour’s implication-realization model (Narmour, 1990, 1992) and cognitive rule-mapping (Narmour, 2000). We introduce the minimum description length scheme as a productive paradigm to support the estimation of S&amp;C descriptions. The S&amp;C model highlights promising connections between music data processing and information retrieval on the one hand, and modern theories in music perception, cognition and semiotics on the other hand, together with interesting perspectives in Musicology.

Reverberation negatively impacts musical sound quality for cochlear implant users

ObjectiveSatisfactory musical sound quality remains a challenge for many cochlear implant (CI) users. In particular, questionnaires completed by CI users suggest that reverberation due to room acoustics can negatively impact their music listening experience. The objective of this study was to more specifically characterize of the effect of reverberation on musical sound quality in CI users, normal hearing (NH) non-musicians, and NH musicians using a previously designed assessment method, called Cochlear Implant-MUltiple Stimulus with Hidden Reference and Anchor (CI-MUSHRA).MethodsIn this method, listeners were randomly presented with an anechoic musical segment and five-versions of this segment in which increasing amounts of reverberation were artificially added. Participants listened to the six reverberation versions and provided sound quality ratings between 0 (very poor) and 100 (excellent).ResultsResults demonstrated that on average CI users and NH non-musicians preferred the sound quality of anechoic versions to more reverberant versions. In comparison, NH musicians could be delineated into those who preferred the sound quality of anechoic pieces and those who preferred pieces with some reverberation.Discussion/ConclusionThis is the first study, to our knowledge, to objectively compare the effects of reverberation on musical sound quality ratings in CI users. These results suggest that musical sound quality for CI users can be improved by non-reverberant listening conditions and musical stimuli in which reverberation is removed.

Perception of basic emotions in music: Culture-specific or multicultural?

The perception of basic emotions such as happy/sad seems to be a human invariant and as such detached from musical experience. On the other hand, there is evidence for cultural specificity: recognition of emotional cues is enhanced if the stimuli and the participants stem from the same culture. A cross-cultural study investigated the following research questions: (1) How are six basic universal emotions (happiness, sadness, fear, disgust, anger, surprise) perceivable in music unknown to listeners with different cultural backgrounds?; and (2) Which particular aspects of musical emotions show similarities and differences across cultural boundaries? In a cross-cultural study, 18 musical segments, representing six basic emotions (happiness, sadness, fear, disgust, anger, surprise) were presented to subjects from Western Europe (Germany and Norway) and Asia (South Korea and Indonesia). Results give evidence for a pan-cultural emotional sentience in music. However, there were distinct cultural, emotion and item-specific differences in emotion recognition. The results are qualified by the outcome measurement procedure since emotional category labels are language-based and reinforce cultural diversity.

Minding the gap: An experimental assessment of musical segmentation models.

Music and language are parallel in many respects (for overviews, see Besson & Friederici, 1998; Patel, 2010), including their origins and historical development (Wallin, Merker, & Brown, 2000), patterns of development across the life span (Drake, 1998), and elements of cognitive processing (Swinney & Love, 1998). Although music and language are different types of stimuli and utilize different cognitive operations (Patel, 1998; Peretz, 1993; Peretz et al., 1994), they appear to share several structural properties (Blacking, 1973; Krumhansl, 1998; Lerdahl & Jackendoff, 1983; Raffman, 1993; Sloboda, 1985). For example, in music and in language, structural rules specify how combinations of smaller units form larger structural frameworks (e.g., notes forming melodies, words forming sentences). However, structural properties of music are more ambiguous and fluid than are structural properties of language (Jackendoff & Lerdahl, 1981; Jescheniak, Hahne, & Friederici, 1998), and the specific structural rules by which a listener might segment a larger musical stimulus into smaller meaningful units are not entirely clear. To better understand the process of musical segmentation, the experiments presented here provide an empirical evaluation of structural rules suggested by two different models of music cognition: the perceived phrase structure model (PPS; Temperley, 2001) and the generative structural grammar of music model (GSGM; Lerdahl & Jackendoff, 1983).Based in part on the notion of generative structural grammars in language (Chomsky, 1965, 1968, 1957/2002; Yngve, 1960), analogous generative structural grammars have been proposed for music (Deutsch & Feroe, 1981; Lerdahl & Jackendoff, 1983; Tenney & Polansky, 1980; Winograd, 1968). The unit of the motif, which can be as small as two notes, is important both structurally and psychologically (see Jackendoff & Lerdahl, 1981; Zbikowski, 1999). Generative grammars combine these motifs into basic phrase units to form the lower level of a hierarchical structure (see Gregory, 1978; Johnson, 1965; Rosenberg, 1968, for empirical support for the functional use of such a structural grammar). Given the fundamental importance of the phrase, and the importance of understanding basic units before proceeding to more complicated hierarchies based on combinations of those basic units, the focus here will be upon segmentation within a local context (i.e., on phrase-level context rather than on extended and hierarchically organized context). To wit, we assessed how participants determine phrase boundaries in musical stimuli and segment those musical stimuli into meaningful parts. There is a paucity of literature assessing segmentation models in diverse (i.e., experienced and inexperienced listener) human (i.e., nonmachine) populations. The relative novelty of our study lies within the populations that we studied and the hypotheses that we tested. Specifically, we studied humans with a range of musical experience and compared their segmentation responses with theoretical segmentation points generated by two prominent musical segmentation theories.The GSGM model is a prominent and influential theory that proposes several grouping preference rules for determining the locations of local context phrase boundaries in music (see Table 1). The GSGM model suggests that when one or more of these grouping rules is fulfilled, then perceived segmentation (i.e., perception of a phrase boundary) typically occurs. The rules are not mutually exclusive, and different rules can be combined to create different strengths or levels of segmentation. Deliege (1987) examined the extent to which perceptual grouping corresponded with the local context segmentation rules of GSGM for a group of listeners. Deliege presented short musical excerpts, and musician or nonmusician participants indicated the point at which they heard natural breaks in the music by drawing a vertical line in a row of horizontally oriented dots in which successive dots represented successive notes. …

Form and Process in Morton Feldman's Spring of Chosroes

AbstractMorton Feldman's Spring of Chosroes is named after a legendary Persian garden carpet. Although it is assumed that the asymmetrical geometric designs of garden carpets inspired the design of the piece, this article is primarily concerned with musical form and process. The music segments into discrete units, which I call modules, that are affiliated by coincident structural features and developmental relationships. The interconnected modules, particularly those that share aspects of pitch, rhythm and register, articulate the work's form. The formal plan is ABA′: section A′ engages the modular structure of section A, and parallelisms in section B create palindromic relationships. Two sets of modules, each of which is connected by developmental processes, make up large‐scale frameworks that reflect the ternary sectional structure and the palindromic design of section B. The music is structurally weighted towards its two central modules, each of which bisects a set of palindromically related modules and, together, the piece as a whole. Organic and inorganic processes unite all levels of form, connecting local and large‐scale structures. Effects of disconnectedness are shown to be surface phenomena arising from the interaction of disparate, ordered structures.

Lateralization of music processing with noises in the auditory cortex: an fNIRS study.

The present study is to determine the effects of background noise on the hemispheric lateralization in music processing by exposing 14 subjects to four different auditory environments: music segments only, noise segments only, music + noise segments, and the entire music interfered by noise segments. The hemodynamic responses in both hemispheres caused by the perception of music in 10 different conditions were measured using functional near-infrared spectroscopy. As a feature to distinguish stimulus-evoked hemodynamics, the difference between the mean and the minimum value of the hemodynamic response for a given stimulus was used. The right-hemispheric lateralization in music processing was about 75% (instead of continuous music, only music segments were heard). If the stimuli were only noises, the lateralization was about 65%. But, if the music was mixed with noises, the right-hemispheric lateralization has increased. Particularly, if the noise was a little bit lower than the music (i.e., music level 10~15%, noise level 10%), the entire subjects showed the right-hemispheric lateralization: This is due to the subjects' effort to hear the music in the presence of noises. However, too much noise has reduced the subjects' discerning efforts.

The KUSC Classical Music Dataset for Audio Key Finding

In this paper, we present a benchmark dataset based on the KUSC classical music collection and provide baseline key-finding comparison results. Audio key finding is a basic music information retrieval task; it forms an essential component of systems for music segmentation, similarity assessment, and mood detection. Due to copyright restrictions and a labor-intensive annotation process, audio key finding algorithms have only been evaluated using small proprietary datasets to date. To create a common base for systematic comparisons, we have constructed a dataset comprising of more than 3,000 excerpts of classical music. The excerpts are made publicly accessible via commonly used acoustic features such as pitch-based spectrograms and chromagrams. We introduce a hybrid annotation scheme that combines the use of title keys with expert validation and correction of only the challenging cases. The expert musicians also provide ratings of key recognition difficulty. Other meta-data include instrumentation. As demonstration of use of the dataset, and to provide initial benchmark comparisons for evaluating new algorithms, we conduct a series of experiments reporting key determination accuracy of four state-of-the-art algorithms. We further show the importance of considering factors such as estimated tuning frequency, key strength or confidence value, and key recognition difficulty in key finding. In the future, we plan to expand the dataset to include meta-data for other music information retrieval tasks.

Usul and Makam driven automatic melodic segmentation for Turkish music

Automatic melodic segmentation is a topic studied extensively, aiming at developing systems that perform grouping of musical events. Here, we consider the problem of automatic segmentation via supervised learning from a dataset containing segmentation labels of an expert. We present a statistical classification-based segmentation system developed specifically for Turkish makam music. The proposed system uses two novel features, a makam-based and an usul-based feature, together with features commonly used in literature. The makam-based feature is defined as the probability of a note to appear at the phrase boundary, computed from the distributions of boundaries with respect to the piece’s makam pitches. Likewise, the usul-based feature is computed from the distributions of boundaries with respect to beats in the rhythmic cycle, usul of the piece. Several experimental setups using different feature groups are designed to test the contribution of the proposed features on three datasets. The results show that the new features carry complementary information to existing features in the literature within the Turkish makam music segmentation context and that the inclusion of new features resulted in statistically significant performance improvement.

The gray matter volume of the amygdala is correlated with the perception of melodic intervals: a voxel-based morphometry study.

Music is not simply a series of organized pitches, rhythms, and timbres, it is capable of evoking emotions. In the present study, voxel-based morphometry (VBM) was employed to explore the neural basis that may link music to emotion. To do this, we identified the neuroanatomical correlates of the ability to extract pitch interval size in a music segment (i.e., interval perception) in a large population of healthy young adults (N = 264). Behaviorally, we found that interval perception was correlated with daily emotional experiences, indicating the intrinsic link between music and emotion. Neurally, and as expected, we found that interval perception was positively correlated with the gray matter volume (GMV) of the bilateral temporal cortex. More important, a larger GMV of the bilateral amygdala was associated with better interval perception, suggesting that the amygdala, which is the neural substrate of emotional processing, is also involved in music processing. In sum, our study provides one of first neuroanatomical evidence on the association between the amygdala and music, which contributes to our understanding of exactly how music evokes emotional responses.

Influences of structure and agency on the perception of musical change.

In previous work, we and others have shown that continuous perceptions of change in an ongoing piece of music can be significant predictors of nonmusicians' continuous perception of the affect expressed by the piece (Bailes & Dean, 2012; Dean & Bailes, 2010), as can other continuous features such as acoustic intensity (Dean, Bailes, & Schubert, 2011; Schubert, 1999, 2004). Yet some evidence has suggested that such nonmusicians are fairly indifferent to large structural features. For example, the global liking of classical music and its perceived expression are little perturbed when sections are shuffled (Eitan & Granot, 2008), when tonal music is presented without tonal closure (Cook, 1987) or after conversion into atonal music of otherwise similar structure (Lalitte, Bigand, Kantor-Martynuska, & Delbe, 2009). This might indicate that musical sections are not explicitly perceived. On the other hand, evidence concerning Roger Reynolds' Angel of Death (for instruments and computer sound) suggests that sectionalisation was indeed perceived in this work (McAdams, Vines, Vieillard, Smith, & Reynolds, 2004). This large-scale concert experiment involved a minority of nonmusicians, but participants could often recognize recurrences of musical material. In this experiment, the task demand to focus continuously on familiarity or resemblance within the piece related explicitly to large-scale structure.The ambiguities in the results just summarized led us to seek to establish whether large-scale musical structures and features of agency (such as solo vs. orchestral sections in a concerto) are reflected in nonmusicians' continuous perceptions of change in music, and to minimize the demand characteristics of the experimental task. Given the disparities about perceptions of large-scale structure under explicit (demand-driven) test conditions, we hypothesized that an impact of large-scale musical structure on continuous perception of local musical change could be detected, and this would provide an implicit measure, without an explicit demand-driven focus on perceiving large-scale structure. Specifically, we hypothesized that large-scale musical segments would predict perceptual response regime-shifts, points which separate segments of different characteristics within the overall response time series. We second hypothesized that such relationships between large-scale musical structure and continuous perception of change would hold within non-Western music, unfamiliar to our nonmusician listeners, as well as in potentially more familiar music. So we investigated this issue with respect to a diverse range of acoustic and electroacoustic pieces from several cultures and periods.Our analysis of continuous perceptual ratings detects statistical in the response time series. This common terminology is slightly misleading: such analyses do not simply detect special features at a particular point, but rather, differences between the overall characteristics of successive segments of the temporal data series. Two of the pieces studied comprise only a single musical segment: if musical segments were the only influence, then no perceptual changepoints would be found in these. However, previous work also shows that surface features, such as short-term changes in acoustic intensity, strongly influence perceived change (Dean & Bailes, 2010); hence, we expect that segments will be perceived in these structurally uniform pieces, and that there will be perceptual segments in the structurally varied works besides those reflecting the musicological structure. The key test of our primary hypothesis is therefore whether the musicological segments coincide with perception changepoints, accepting that additional changepoints may be expected.One might theorise that inexperienced listeners would lack the ability to group and hierarchically organize the low-level features of the music as it flows: they might not be able to transform perceptions at a fine-grained temporal resolution (continuous change) into those in a larger time frame (musical structure). …