Godel, Escher, Bach: An Eternal Golden Braid

This book addresses the central problem of music cognition: how listeners' responses move beyond mere registration of auditory events to include the organization, interpretation, and remembrance of these events in terms of their function in a musical context of pitch and rhythm. Equally important, the work offers an analysis of the relationship between the psychological organization of music and its internal structure. Combining over a decade of original research on music cognition with an overview of the available literature, the work will be of interest to cognitive and physiological psychologists, psychobiologists, musicians, music researchers, and music educators.

Cognitive Foundations Of Musical Pitch

Hydrogenated Amorphous Silicon

In modern societies, cultural change seems ceaseless. The flux of fashion is especially obvious for popular music. While much has been written about the origin and evolution of pop, most claims about its history are anecdotal rather than scientific in nature. To rectify this, we investigate the US Billboard Hot 100 between 1960 and 2010. Using music information retrieval and text-mining tools, we analyse the musical properties of approximately 17 000 recordings that appeared in the charts and demonstrate quantitative trends in their harmonic and timbral properties. We then use these properties to produce an audio-based classification of musical styles and study the evolution of musical diversity and disparity, testing, and rejecting, several classical theories of cultural change. Finally, we investigate whether pop musical evolution has been gradual or punctuated. We show that, although pop music has evolved continuously, it did so with particular rapidity during three stylistic ‘revolutions’ around 1964, 1983 and 1991. We conclude by discussing how our study points the way to a quantitative science of cultural change.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.150081

The evolution of popular music: USA 1960–2010

Underdense hydrogenated amorphous silicon (a-Si:H) prepared by plasma-enhanced chemical vapor deposition was used as a passivation layer in silicon heterojunction (SHJ) solar cells. By reducing the thickness of the underdense a-Si:H passivation layer from 15 nm to 5 nm, the open circuit voltage (Voc) of the corresponding SHJ solar cell increased significantly from 724.3 mV to 738.6 mV. For comparison, a widely used transition-zone a-Si:H passivation layer was also examined, but reducing its thickness from 15 nm to 5 nm resulted in a continuous Voc reduction, from 724.1 mV to 704.3 mV. The highest efficiency was achieved using a 5-nm-thick underdense a-Si:H passivation layer. We propose that this advantageous property of underdense a-Si:H reflects its microstructural characteristics. While the porosity of a-Si:H layer enables H penetration into the amorphous network and the a-Si:H/c-Si interface, a high degree of disorder inhibits the formation of the epitaxial layer at the a-Si:H/c-Si interface during pos...

Underdense a-Si:H film capped by a dense film as the passivation layer of a silicon heterojunction solar cell

In musicology, there has been a long debate about a meaningful partitioning and description of music history regarding composition styles. Particularly, concepts of historical periods have been cri...

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Investigating style evolution of Western classical music: A computational approach:

Choral singing is a central part of musical cultures across the world, yet many facets of this widespread form of polyphonic singing are still to be explored. Music information retrieval (MIR) research on choral singing benefits from multitrack recordings of the individual singing voices. However, there exist only few publicly available multitrack datasets on polyphonic singing. In this paper, we present Dagstuhl ChoirSet (DCS), a multitrack dataset of a cappella choral music designed to support MIR research on choral singing. The dataset includes recordings of an amateur vocal ensemble performing two choir pieces in full choir and quartet settings. The audio data was recorded during an MIR seminar at Schloss Dagstuhl using different close-up microphones to capture the individual singers’ voices. In this article, we give detailed insights into all stages of creating DCS: recording process, data preparation, generation of annotations as well as development of suitable interfaces for publicly accessing and reusing the data. Furthermore, we demonstrate the potential of the dataset for MIR research by discussing case studies on choral intonation assessment and multiple fundamental frequency (F0) estimation.

/pdf/dagstuhl-choirset-a-multitrack-dataset-for-mir-research-on-jg21q6lkjx.pdf

Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing

This paper approaches the problem of annotating measure positions in Western classical music recordings. Such annotations can be useful for navigation, segmentation, and cross-version analysis of music in different types of representations. In a case study based on Wagner’s opera “Die Walküre”, we analyze two types of annotations. First, we report on an experiment where several human listeners generated annotations in a manual fashion. Second, we examine computer-generated annotations which were obtained by using score-to-audio alignment techniques. As one main contribution of this paper, we discuss the inconsistencies of the different annotations and study possible musical reasons for deviations. As another contribution, we propose a kernel-based method for automatically estimating confidences of the computed annotations which may serve as a first step towards improving the quality of this automatic method.

Analyzing Measure Annotations for Western Classical Music Recordings.

While global key and chord estimation for both popular and classical music recordings have received a lot of attention, little research has been devoted to estimating the local key for classical music. Partly, this may be due to its inherent ambiguity and subjectivity, which makes annotating local keys a challenging task. In this article, we approach local key estimation with a cross-version dataset comprising nine performances (versions) of Schubert's song cycle Winterreise annotated by three different music theory experts. We consider two baseline methods that are representative for common types of signal processing algorithms: an HMM-based system and a CNN-based approach. For both models, we employ a similar training procedure including the optimization of hyperparameters on a validation split. We systematically evaluate the model predictions and provide musical explanations for key confusions. As a central contribution, we explore how different training–test splits affect the models’ efficacy. Splitting along the song axis, we find that both methods perform similarly well. Splitting along the version axis, we obtain substantially higher accuracies, especially for the CNN, which seems to effectively learn the harmonic progressions of the songs (“cover song effect”) and successfully generalizes to unseen versions. We further discuss the results for several songs in detail and assess our results from the perspective of multiple annotators. This cross-annotator study reveals that a substantial part of the systems’ errors coincides with annotator disagreement and an even larger part can be traced back to musically explainable relationships among different keys.

Local Key Estimation in Music Recordings: A Case Study Across Songs, Versions, and Annotators

This article presents a multimodal dataset comprising various representations and annotations of Franz Schubert’s song cycle Winterreise. Schubert’s seminal work constitutes an outstanding example of the Romantic song cycle—a central genre within Western classical music. Our dataset unifies several public sources and annotations carefully created by music experts, compiled in a comprehensive and consistent way. The multimodal representations comprise the singer’s lyrics, sheet music in different machine-readable formats, and audio recordings of nine performances, two of which are freely accessible for research purposes. By means of explicit musical measure positions, we establish a temporal alignment between the different representations, thus enabling a detailed comparison across different performances and modalities. Using these alignments, we provide for the different versions various musicological annotations describing tonal and structural characteristics. This metadata comprises chord annotations in different granularities, local and global annotations of musical keys, and segmentations into structural parts. From a technical perspective, the dataset allows for evaluating algorithmic approaches to tasks such as automated music transcription, cross-modal music alignment, or tonal analysis, and for testing these algorithms’ robustness across songs, performances, and modalities. From a musicological perspective, the dataset enables the systematic study of Schubert’s musical language and style in Winterreise and the comparison of annotations regarding different annotators and granularities. Beyond the research domain, the data may serve further purposes such as the didactic preparation of Schubert’s work and its presentation to a wider public by means of an interactive multimedia experience. With this article, we provide a detailed description of the dataset, indicate its potential for computational music analysis by means of several studies, and point out possibilities for future research.

https://dl.acm.org/doi/pdf/10.1145/3429743

Christof Weiß

Papers

Investigating style evolution of Western classical music: A computational approach:

Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing

Analyzing Measure Annotations for Western Classical Music Recordings.

Local Key Estimation in Music Recordings: A Case Study Across Songs, Versions, and Annotators

Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis