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 objective function (L>1) and are caused positive utilitarian emotions. Minor chords are expressed as the inverse proportion, which generate idea about the decrease of objective function (L<1) and are caused negative utilitarian emotions.
The formula of musical emotions is advanced: Pwe = log(L) = (1/M)*log(n1*n2*n3* ... *nM), where M is a quantity of voices of chord, ni - integer number (or reciprocal fraction) from the pitch proportion, which corresponds to the i-th voice of chord.
Confined experimental check is produced. The limits of the applicability of the formula of musical emotions are investigated.
Keywords: sound, music, chord, major, minor, emotions, the formula of musical emotions, the information theory of emotions.
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 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…
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…
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…
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）
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…
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 …
Escuela Politécnica Superior（高等理工学院）；Universidad Autónoma de Madrid（马德里自治大学）
Understanding the structural characteristics of harmony is essential for an effective use of music as a communication medium. Of the three expressive axes of music (melody, rhythm, harmony), harmony is the foundation on which the emotional content is built, and its understanding is important in areas such as multimedia and affective computing. The common tool for studying this kind of structure in computing science is the formal grammar but, in the case of music, grammars run into problems due to the ambiguous nature of some of the concepts defined in music theory. In this paper, we consider o…
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…
School of Electrical and Computer Engineering（电气与计算机工程学院）；University of Campinas（坎皮纳斯大学）
When songs are composed or performed, there is often an intent by the singer/songwriter of expressing feelings or emotions through it. For humans, matching the emotiveness in a musical composition or performance with the subjective perception of an audience can be quite challenging. Fortunately, the machine learning approach for this problem is simpler. Usually, it takes a data-set, from which audio features are extracted to present this information to a data-driven model, that will, in turn, train to predict what is the probability that a given song matches a target emotion. In this paper, we…
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…
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…
Sir C.V. Raman Centre for Physics and Music（C.V. 拉曼爵士物理与音乐中心）；Jadavpur University（贾达普大学）
In North Indian Classical Music, raga forms the basic structure over which individual improvisations is performed by an artist based on his/her creativity. The Alap is the opening section of a typical Hindustani Music (HM) performance, where the raga is introduced and the paths of its development are revealed using all the notes used in that particular raga and allowed transitions between them with proper distribution over time. In India, corresponding to each raga, several emotional flavors are listed, namely erotic love, pathetic, devotional, comic, horrific, repugnant, heroic, fantastic, fu…
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…
