The paper offers a solution to the centuries-old puzzle - why the major chords are perceived as happy and the minor chords as sad - based on the information theory of emotions. A theory and a formula of musical emotions were created. They define the sign and the amplitude of the utilitarian emotional coloration of separate major and minor chords through relative pitches of constituent sounds. Keywords: chord, major, minor, the formula of musical emotions, the information theory of emotions.
The new formulas, which determine sign and amplitude of utilitarian emotions, are proposed on the basis of the information theory of emotions. In area of perception of musical chords the force of emotions depends on the relative pitch of sounds of major and minor chords. Is advanced hypothesis that in the perception of a musical chord in the psyche caused by the subject value of some objective function L. This function is expressed directly through the proportion of the pitch of chord. Major chords are expressed as the straight proportions, which generate idea about an increase in the objectiv…
In this paper we present a mathematical way of defining musical modes and we define the musicality of a mode as a product of three different factors. We conclude by classifying the modes which are most musical according to our definition.
Indiana University（印第安纳大学）；Santa Fe Institute（圣塔菲研究所）
We investigate the association between musical chords and lyrics by analyzing a large dataset of user-contributed guitar tablatures. Motivated by the idea that the emotional content of chords is reflected in the words used in corresponding lyrics, we analyze associations between lyrics and chord categories. We also examine the usage patterns of chords and lyrics in different musical genres, historical eras, and geographical regions. Our overall results confirms a previously known association between Major chords and positive valence. We also report a wide variation in this association across r…
Chord recognition systems depend on robust feature extraction pipelines. While these pipelines are traditionally hand-crafted, recent advances in end-to-end machine learning have begun to inspire researchers to explore data-driven methods for such tasks. In this paper, we present a chord recognition system that uses a fully convolutional deep auditory model for feature extraction. The extracted features are processed by a Conditional Random Field that decodes the final chord sequence. Both processing stages are trained automatically and do not require expert knowledge for optimising parameters…
The term jitter and shimmer has long been used in the domain of speech and acoustic signal analysis as a parameter for speaker identification and other prosodic features. In this study, we look forward to use the same parameters in neural domain to identify and categorize emotional cues in different musical clips. For this, we chose two ragas of Hindustani music which are conventionally known to portray contrast emotions and EEG study was conducted on 5 participants who were made to listen to 3 min clip of these two ragas with sufficient resting period in between. The neural jitter and shimmer…
Ircam（法国声学/音乐研究和协作学院）；CNRS（法国国家科学研究中心）；University of La Rochelle（拉罗谢尔大学）
Recent researches on Automatic Chord Extraction (ACE) have focused on the improvement of models based on machine learning. However, most models still fail to take into account the prior knowledge underlying the labeling alphabets (chord labels). Furthermore, recent works have shown that ACE performances are converging towards a glass ceiling. Therefore, this prompts the need to focus on other aspects of the task, such as the introduction of musical knowledge in the representation, the improvement of the models towards more complex chord alphabets and the development of more adapted evaluation …
We propose a new way of analyzing musical pieces by using the exceptional musical icosahedra where all the major/minor triads are represented by golden triangles or golden gnomons. First, we introduce a concept of the golden neighborhood that characterizes golden triangles/gnomons that neighbor a given golden triangle or gnomon. Then, we investigate a relation between the exceptional musical icosahedra and the neo-Riemannian theory, and find that the golden neighborhoods and the icosahedron symmetry relate any major/minor triad with any major/minor triad. Second, we show how the exceptional mu…
Vellore Institute of Technology（韦洛尔理工学院）；Indian Institute of Technology Madras（印度理工学院马德拉斯分校）
In classical music and in any genre of contemporary music, the tonal elements or notes used for playing are the same. The numerous possibilities of chords for a given instance in a piece make the playing, in general, very intricate, and advanced. The theory sounds quite trivial, yet the application has vast options, each leading to inarguably different outcomes, characterized by scientific and musical principles. Chords and their importance are self-explanatory. A chord is a bunch of notes played together. As far as scientists are concerned, it is a set of tonal frequencies ringing together re…
Chord recognition is an important task since chords are highly abstract and descriptive features of music. For effective chord recognition, it is essential to utilize relevant context in audio sequence. While various machine learning models such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been employed for the task, most of them have limitations in capturing long-term dependency or require training of an additional model. In this work, we utilize a self-attention mechanism for chord recognition to focus on certain regions of chords. Training of the propose…
The task of classifying emotions within a musical track has received widespread attention within the Music Information Retrieval (MIR) community. Music emotion recognition has traditionally relied on the use of acoustic features, verbal features, and metadata-based filtering. The role of musical prosody remains under-explored despite several studies demonstrating a strong connection between prosody and emotion. In this study, we restrict the input of traditional machine learning algorithms to the features of musical prosody. Furthermore, our proposed approach builds upon the prior by classifyi…
Discovering and exploring the underlying structure of multi-instrumental music using learning-based approaches remains an open problem. We extend the recent MusicVAE model to represent multitrack polyphonic measures as vectors in a latent space. Our approach enables several useful operations such as generating plausible measures from scratch, interpolating between measures in a musically meaningful way, and manipulating specific musical attributes. We also introduce chord conditioning, which allows all of these operations to be performed while keeping harmony fixed, and allows chords to be cha…
EMelodyGen: Emotion-Conditioned Melody Generation in ABC Notation with the Musical Feature Template
Department of Music AI and Information Technology, Central Conservatory of Music（中央音乐学院音乐人工智能与信息科技系）；School of Computer Science and Technology, Fudan University（复旦大学计算机科学与技术学院）；Shanghai Key Laboratory of Intelligent Information Processing, Fudan University（复旦大学智能信息处理上海重点实验室）
Structure perception is a fundamental aspect of music cognition in humans. Historically, the hierarchical organization of music into structures served as a narrative device for conveying meaning, creating expectancy, and evoking emotions in the listener. Thereby, musical structures play an essential role in music composition, as they shape the musical discourse through which the composer organises his ideas. In this paper, we present a novel music segmentation method, pitchclass2vec, based on symbolic chord annotations, which are embedded into continuous vector representations using both natur…
Variational Quantum Harmonizer: Generating Chord Progressions and Other Sonification Methods with the VQE Algorithm
Interdisciplinary Centre for Computer Music Research -- University of Plymouth（普利茅斯大学跨学科计算机音乐研究中心）；Centre for Quantum Technologies and Applications -- Deutsches Elektronen-Synchrotron DESY（德国电子同步加速器中心量子技术与应用中心）；Music Technology Group -- Pompeu Fabra University（庞培法布拉大学音乐技术组）
The perception of consonance/dissonance of musical harmonies is strongly correlated with their periodicity. This is shown in this article by consistently applying recent results from psychophysics and neuroacoustics, namely that the just noticeable difference between pitches for humans is about 1% for the musically important low frequency range and that periodicities of complex chords can be detected in the human brain. Based thereon, the concepts of relative and logarithmic periodicity with smoothing are introduced as powerful measures of harmoniousness. The presented results correlate signif…
Music is an expressive form of communication often used to convey emotion in scenarios where "words are not enough". Part of this information lies in the musical composition where well-defined language exists. However, a significant amount of information is added during a performance as the musician interprets the composition. The performer injects expressiveness into the written score through variations of different musical properties such as dynamics and tempo. In this paper, we describe a model that can learn to perform sheet music. Our research concludes that the generated performances are…
Johannes Kepler University（约翰·开普勒大学）；Linz Institute of Technology（林茨理工学院）
Music emotion recognition is an important task in MIR (Music Information Retrieval) research. Owing to factors like the subjective nature of the task and the variation of emotional cues between musical genres, there are still significant challenges in developing reliable and generalizable models. One important step towards better models would be to understand what a model is actually learning from the data and how the prediction for a particular input is made. In previous work, we have shown how to derive explanations of model predictions in terms of spectrogram image segments that connect to …
Tampere University of Technology（坦佩雷理工大学）；University of Zilina（日利纳大学）
This paper studies the emotion recognition from musical tracks in the 2-dimensional valence-arousal (V-A) emotional space. We propose a method based on convolutional (CNN) and recurrent neural networks (RNN), having significantly fewer parameters compared with the state-of-the-art method for the same task. We utilize one CNN layer followed by two branches of RNNs trained separately for arousal and valence. The method was evaluated using the 'MediaEval2015 emotion in music' dataset. We achieved an RMSE of 0.202 for arousal and 0.268 for valence, which is the best result reported on this dataset…
Emotion and expressivity in music have been topics of considerable interest in the field of music information retrieval. In recent years, mid-level perceptual features have been suggested as means to explain computational predictions of musical emotion. We find that the diversity of musical styles and genres in the available dataset for learning these features is not sufficient for models to generalise well to specialised acoustic domains such as solo piano music. In this work, we show that by utilising unsupervised domain adaptation together with receptive-field regularised deep neural networ…
