Music Mood Research Articles

Musical creativity and mood bipolarity in Robert Schumann: A tribute on the 200th anniversary of the composer's birth

Musical creativity and mood bipolarity in Robert Schumann: A tribute on the 200th anniversary of the composer's birth

Query-by-Example Music Information Retrieval by Score-Informed Source Separation and Remixing Technologies

We describe a novel query-by-example (QBE) approach in music information retrieval that allows a user to customize query examples by directly modifying the volume of different instrument parts. The underlying hypothesis of this approach is that the musical mood of retrieved results changes in relation to the volume balance of different instruments. On the basis of this hypothesis, we aim to clarify the relationship between the change in the volume balance of a query and the genre of the retrieved pieces, called genre classification shift. Such an understanding would allow us to instruct users in how to generate alternative queries without finding other appropriate pieces. Our QBE system first separates all instrument parts from the audio signal of a piece with the help of its musical score, and then it allows users remix these parts to change the acoustic features that represent the musical mood of the piece. Experimental results showed that the genre classification shift was actually caused by the volume change in the vocal, guitar, and drum parts.

Relationship between the effect of musical mood induction and aggression

Relationship between the effect of musical mood induction and aggression

Negative mood, implicit alcohol-related memory, and alcohol use in young adults: The moderating effect of alcohol expectancy

Objective Alcohol-related implicit (preconscious) cognitive processes are established and unique predictors of alcohol use, but most research in this area has focused on alcohol-related implicit cognition and anxiety. This study extends this work into the area of depressed mood by testing a cognitive model that combines traditional explicit (conscious and considered) beliefs, implicit alcohol-related memory associations (AMAs), and self-reported drinking behavior. Method Using a sample of 106 university students, depressed mood was manipulated using a musical mood induction procedure immediately prior to completion of implicit then explicit alcohol-related cognition measures. A bootstrapped two-group (weak/strong expectancies of negative affect and tension reduction) structural equation model was used to examine how mood changes and alcohol-related memory associations varied across groups. Results Expectancies of negative affect moderated the association of depressed mood and AMAs, but there was no such association for tension reduction expectancy. Conclusion Subtle mood changes may unconsciously trigger alcohol-related memories in vulnerable individuals. Results have implications for addressing subtle fluctuations in depressed mood among young adults at risk of alcohol problems.

Kabīr reconstructed

On the example of some texts attributed to the 15th-century poet-saint Kabīr, the paper contests the postmodern claim that each received version is a poetically beautiful, polished text. In all probability all received versions have undergone a long phase of oral transmission before being committed to writing and they are sometimes the outcome of textual corruption resulting in inconsistent reading or in poetic looseness and redundancy. On the basis of prosody and a comparison of variant versions, reconstruction of some earlier text is possible. It is argued that the poems may have been composed for a metrically correct recitation and when they became songs set to musical moods and rhythms they have lost their strict metrical frame under the licenses used by the singers. Amplification can also be detected on a higher level since sometimes entire lines were invented or borrowed. By detecting instances of amplification a more concise and more powerful early text can be reconstructed. The reconstruction of the early text in turn can open up a way to posit the later variants into a relationship with each other and to see ideological motivating forces behind changes such as ‘bhaktification’.

상황인지 음악추천을 위한 음악 분위기 검출

상황인지 음악추천 서비스를 제공하기 위해서는 무엇보다 상황 또는 문맥에 따라 사용자가 선호하는 음악의 분위기를 파악할 필요가 있다. 음악 분위기 검출에 대한 기존 연구의 대부분은 수작업으로 대표구간을 선정하고, 그 구간의 특징을 이용하여 분위기를 판별한다. 이러한 접근 방법은 분류 성능이 좋은 반면 전문가의 간섭을 요구하기 때문에 새로운 음악에 대해서는 적용하기 어렵다. 더욱이, 곡의 진행에 따라 음악 분위기가 달라지기 때문에 음악의 대표 분위기를 검출하는 것이 더욱 어려워진다. 본 논문에서는 이러한 문제점들을 보완하기 위해 음악 분위기를 자동으로 판별하는 새로운 방법을 제안하였다. 먼저 곡 전체를 구조적 분석 방법을 통하여 비슷한 특성을 갖는 세그먼트들로 분리한 후 각각에 대해 분위기를 판별한다. 그리고 세그먼트별 분위기 파악 시 Thayer 의 2차원 분위기 모델에 기초한 회귀분석 방법으로 개인별 주관적 분위기 성향을 모델링하였다. 실험결과, 제안된 방법이 80% 이상의 정확도를 보였다. To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.

사용자의 취향을 고려한 음악 재생 목록 생성 시스템

음악의 생산과 수요 증가와 함께 사용자의 장치에 저장되어 있는 음악을 관리하기 위한 관심 또한 증가하고 있다. 일반적으로 사용자는 음악을 효과적으로 관리하기 위해 재생 목록을 작성하고 이를 선택하는 방법을 사용하고 있다. 하지만 현재 사용되는 재생 목록의 작성 방법은 음악을 사용자가 직접 선택해야 하는 한계를 안고 있다. 따라서 재생 목록을 자동으로 작성하여 사용자에게 제공해주는 방법이 필요하다. 본 논문에서는 사용자의 음악사용의 상황과 취향을 고려하여 자동으로 재생 목록을 생성해주는 시스템을 제안한다. 이 시스템은 음악적 무드 (Musical mood) 분류 시스템과 음악 추천 시스템, 두 가지 별개의 시스템으로 구성되어 있다. 사용자는 음악을 추천 받기 위해 단지 하나의 음악을 선택한다. 그러면 시스템은 자동으로 재생 목록을 생성하기 위해 선택된 음악과 유사한 무드의 음악을 재생 목록에 추가한다. 사용자는 재생 목록에 추가된 음악 중 자신의 취향에 맞지 않는 음악을 제거하여 취향에 적합한 음악을 반복적으로 추천 받을 수 있다. 본 논문에서 제안하는 시스템의 실험과 평가를 위해 실제 음악을 수집하였으며 시스템을 통해 생성된 재생 목록을 분석하여 사용자의 취향이 보다 정확히 반영된 것을 확인하였다. The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user's context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.

Autism, Music, and the Therapeutic Potential of Music in Alexithymia

IT HAS BEEN ARGUED, IN VIEW OF THE SOCIAL evolutionary origins of music and the social deficits found in autism, that individuals with autism will be emotionally unresponsive to music. However, a recent study of high-functioning adults with autism has shown that they appear to have a range of responses to music similar to typically developing people, including the deliberate use of music for mood management. In examining why these responses appear unaffected in autism, we explore possible mechanisms for musical mood induction in listeners, hypothesizing that the simulation theory of empathy may illuminate current controversies over the nature of emotion in music. Drawing on these ideas, we put forward suggestions for using a simple associative learning process between musically induced emotions and their cognitive correlates for the clinical treatment of alexithymia, a disorder that is common in autism and characterized by an absence of cognitive insight into one's emotions.

Music Retrieval and Recommendation Scheme Based on Varying Mood Sequences

A typical music clip consists of one or more segments with different moods and such mood information could be a crucial clue for determining the similarity between music clips. One representative mood has been selected for music clip for retrieval, recommendation or classification purposes, which often gives unsatisfactory result. In this paper, the authors propose a new music retrieval and recommendation scheme based on the mood sequence of music clips. The authors first divide each music clip into segments through beat structure analysis, then, apply the k-medoids clustering algorithm for grouping all the segments into clusters with similar features. By assigning a unique mood symbol for each cluster, one can transform each music clip into a musical mood sequence. For music retrieval, the authors use the Smith-Waterman (SW) algorithm to measure the similarity between mood sequences. However, for music recommendation, user preferences are retrieved from a recent music playlist or user interaction through the interface, which generates a music recommendation list based on the mood sequence similarity. The authors demonstrate that the proposed scheme achieves excellent performance in terms of retrieval accuracy and user satisfaction in music recommendation.

‘Mister D.J., Cheer Me Up!’: Musical and Textual Features for Automatic Mood Classification

Mass consumption of large collections of digital music asks for efficient and intuitive ways of organization. In this article, a system is presented which recognizes the evoked music mood on the basis of a wide variety of features, closely sticking to real world conditions. A two-dimensional mood model is discussed in which moods resemble binary values for arousal and valence and an easy and thus user-friendly method is presented through which a fuzzy seven-class mood cluster is deducted. The songs of the ‘Twenty Years of MTV Europe Most Wanted’ music database consisting of recorded pop music tracks serve for evaluation of three groups of features: firstly, traditional features such as rhythm and tonal features, zero crossing rate, cepstral, and MPEG-7 Low Level Descriptors for audio content are extracted. Secondly, lyrics, chord sequences, and genre data are obtained from on-line sources. Thirdly, from all these, the high-level features, musical mode, and as a novel feature, the suited ballroom dance style, are created automatically. The features selected are data-driven, and Support Vector Machines are used for classification. Prediction accuracies of 77.4% for arousal and 72.9% for valence as well as 71.8% (including neighbours) for the seven-class cluster model are obtained pre-serving realism in terms of non-prototypical music selection and feature extraction throughout.

Hierarchical Clustering of Music towards Human Mood

This paper presents the methods for mining the music, based on mood dimension. Mood is an emerging metadata type and access point in music digital libraries (MDL) and online music repositories. There is a growing interest in developing and evaluating Music Information Retrieval (MIR) systems that can provide automated access to the mood dimension of music. Music is nice thing to all. Mood as a music access feature that is not well understood as well as not standardized. To better understanding we develop method to evaluate automated mood access techniques. This paper explore the relationships that mood has with genre, artist and usage metadata. There is an important consistency within the genre-mood and artist-mood relationships. These consistencies lead to us to develop a cluster based approach by creating a relatively small set of data derived. The emotional component of music has been recognized as the most important factor. Music information behavior studies have also identified music mood as an important criterion used by people in music. Music evokes various human emotions or creates music moods through low level musical features. In fact, typical music consists of one or more moods and this can be used as an important factor for determining the similarity between music. In this paper, we propose a new music retrieval scheme based on the mood change pattern. Keywords: music mood classification, audio features, mood labels.

Indexing music by mood: design and integration of an automatic content-based annotator

In the context of content analysis for indexing and retrieval, a method for creating automatic music mood annotation is presented. The method is based on results from psychological studies and framed into a supervised learning approach using musical features automatically extracted from the raw audio signal. We present here some of the most relevant audio features to solve this problem. A ground truth, used for training, is created using both social network information systems (wisdom of crowds) and individual experts (wisdom of the few). At the experimental level, we evaluate our approach on a database of 1,000 songs. Tests of different classification methods, configurations and optimizations have been conducted, showing that Support Vector Machines perform best for the task at hand. Moreover, we evaluate the algorithm robustness against different audio compression schemes. This fact, often neglected, is fundamental to build a system that is usable in real conditions. In addition, the integration of a fast and scalable version of this technique with the European Project PHAROS is discussed. This real world application demonstrates the usability of this tool to annotate large-scale databases. We also report on a user evaluation in the context of the PHAROS search engine, asking people about the utility, interest and innovation of this technology in real world use cases.

Is manipulation of mood a critical component of cognitive bias modification procedures?

This paper investigates whether changes in mood state are an important component of cognitive bias modification (CBM) procedures. In a novel CBM procedure participants read either positive or negative statements relating to social issues for 5 min. Interpretation bias was measured by means of a scrambled sentence test, which was presented both before and after the CBM procedure. Participants who read the positive statements made more positive resolutions to the scrambled sentences, while participants who read the negative statements made more negative resolutions. Thus, the appropriate positive and negative interpretative biases were induced by the CBM procedure. However, significant mood changes also occurred following CBM. In Experiment 2, a musical mood induction procedure was presented with depressing or elating music. As before, a scrambled sentence test was presented both before and after the musical mood induction. Mood changed in accordance with the valence of the music to the same extent as with CBM. Critically however, performance on the scrambled sentence task did not change for both groups. This demonstrates that a change in mood state is not sufficient for a change in cognitive bias to occur.

Embodiment of Sadness and Depression—Gait Patterns Associated With Dysphoric Mood

To analyze gait patterns associated with sadness and depression. Embodiment theories suggest a reciprocal relationship between bodily expression and the way in which emotions are processed. In Study 1, the gait patterns of 14 inpatients suffering from major depression were compared with those of matched never-depressed participants. In Study 2, we employed musical mood induction to induce sad and positive mood in a sample of 23 undergraduates. A Fourier-based description of walking data served as the basis for the computation of linear classifiers and for the analysis of gait parameters. Gait patterns associated with sadness and depression are characterized by reduced walking speed, arm swing, and vertical head movements. Moreover, depressed and sad walkers displayed larger lateral swaying movements of the upper body and a more slumped posture. The results of the present study indicate that a specific gait pattern characterizes individuals in dysphoric mood.

Categorizing music mood in social context

AbstractMusic mood is an emerging metadata type of music, but there are no well‐accepted mood categories. This research proposes a new method to categorize music mood in the social context of music listening. This method combines the strength of social tags, linguistic resources and human experts. Preliminary results show that the proposed method is promising in identifying mood categories that better reflect users' actual music information behaviors.

Relationships Between Alcohol-Related Memory Association and Changes in Mood: Systematic Differences Between High- and Low-Risk Drinkers

Heavy alcohol use is common in undergraduates and is associated with health-risk behaviors, negative consequences, and increased risk for future alcohol dependence. Alcohol-related memory associations (AMAs) and mood changes are independently related to student drinking, but more research on how these variables interact is needed. To examine (i) how AMAs predict drinking behavior after accounting for depression, and (ii) how changes in negative and positive mood predict AMAs among low- and high-risk drinkers. Positive and negative moods were manipulated using a musical mood induction procedure immediately prior to completion of memory association measures. A bootstrapped structural equation model was tested, permitting a sampling distribution free of the requirement of normality. Negative mood changes predicted AMAs in high-risk drinkers but not in low-risk drinkers, and the opposite was found for positive mood changes. The negative mood-AMA association appeared related to risky drinking, and these subtle implicit cognitive processes may warrant a special focus in intervention programs for high-risk drinkers.

Procédures d’induction d’humeurs en laboratoire : une revue critique

Resume Le regain d’interet des chercheurs pour l’etude des relations entre cognition et emotion a conduit au developpement de nombreuses techniques d’induction d’humeurs. Cet article a pour objectifs d’effectuer une revue des principales procedures d’induction d’humeurs developpees depuis l’etude princeps de Schachter et Singer [Psychol Rev 69 (1962) 379–399] et de rendre compte de l’interet mais aussi des inconvenients lies a l’utilisation de telles techniques. La litterature dans ce domaine est tres importante et l’objectif ici n’est pas d’en rendre compte de maniere exhaustive mais plutot de preciser les principales procedures permettant l’induction d’une humeur negative comme d’une humeur positive. Dans un premier temps, seront donc detaillees les differentes procedures selon leur caractere simple (utilisation d’une seule modalite d’induction) ou composite (association de deux techniques simples). Dans un second temps, il s’agira de presenter l’utilite de l’induction d’humeurs dans l’etude du fonctionnement cognitif normal et pathologique puis de revenir sur les problemes inherents a l’emploi de l’induction d’humeurs tant du point de vue des effets de demande frequemment generes que du point de vue de l’efficacite des inductions realisees.

Role of tempo entrainment in psychophysiological differentiation of happy and sad music?

Respiration rate allows to differentiate between happy and sad excerpts which may be attributable to entrainment of respiration to the rhythm or the tempo rather than to emotions [Etzel, J.A., Johnsen, E.L., Dickerson, J., Tranel, D., Adolphs, R., 2006. Cardiovascular and respiratory responses during musical mood induction. Int. J. Psychophysiol. 61(1), 57–69]. In order to test for this hypothesis, this study intended to verify whether fast and slow rhythm, and/or tempo alone are sufficient to induce differential physiological effects. Psychophysiological responses (electrodermal responses, facial muscles activity, blood pressure, heart and respiration rate) were then measured in fifty young adults listening to fast/happy and slow/sad music, and to two control versions of these excerpts created by removing pitch variations (rhythmic version) and both pitch and temporal variations (beat-alone). The results indicate that happy and sad music are significantly differentiated (happy > sad) by diastolic blood pressure, electrodermal activity, and zygomatic activity, while the fast and slow rhythmic and tempo control versions did not elicit such differentiations. In contrast, respiration rate was faster with stimuli presented at fast tempi relative to slow stimuli in the beat-alone condition. It was thus demonstrated that the psychophysiological happy/sad distinction requires the tonal variations and cannot be explained solely by entrainment to tempo and rhythm. The tempo entrainment exists in the tempo alone condition but our results suggest this effect may disappear when embedded in music or with rhythm.

A Musical Mood Induction Alleviates Dysfunctional Attitudes in Needy and Self-Critical Individuals

The “mood-state hypothesis” (Miranda & Persons, 1988) suggests that dysfunctional beliefs are latent in individuals vulnerable to depression until activated by a negative mood. The purpose of the current study was twofold: (a) to validate a new musical mood induction procedure and (b) to test the cognitive reactivity (or changes in the endorsement of dysfunctional beliefs) in individuals hypothesized to be vulnerable to depression (Blatt, Zohar, Quinlan, Zuroff, & Mongrain, 1995). The mood induction procedure was found to be highly effective for both the positive and the negative conditions. Needy and self-critical participants reported increases in the endorsement of dysfunctional attitudes with the depressing music. With the elating music, needy and self-critical participants experiencing an increase in happiness reported lower levels of dysfunctional attitudes. The findings support state-trait models of depressive vulnerability (Zuroff, Blatt, Sanislow, & Bondi, 1999) and further illustrate how positive mood states can ameliorate the report of maladaptive thoughts.

The mood-induced activation of implicit alcohol cognition in enhancement and coping motivated drinkers

In two experiments, we investigated whether different mood states activate specific types of implicit alcohol cognition among undergraduates classified as enhancement (EM) or coping (CM) motivated drinkers. Participants completed a Stroop task in Experiment 1 ( n = 81), and an Extrinsic Affective Simon Task (EAST; [De Houwer, J. (2003). The Extrinsic Affective Simon Task. Experimental Psychology, 50, 77–85.]) in Experiment 2 ( n = 79) following random assignment to listen to positive or negative musical mood induction procedures (MMIP). Consistent with hypotheses, only EM, and not CM, drinkers displayed an activation of implicit attention to alcohol cues (Experiment 1) and reward-alcohol implicit associations (Experiment 2) following exposure to positive MMIP. Contrary to hypotheses for CM drinkers, none of the groups, in either experiment, showed an activation of implicit alcohol processing following exposure to negative MMIP. Confidence that positive mood activates implicit alcohol cognition among EM drinkers is increased since this result emerged across two studies involving quite different methodologies. This research has implications for experimental cognitive research and it highlights the potential utility of treatment matching according to drinking motives (e.g., EM) to improve clinical outcomes.