Music Playlists Research Articles

Follow your heart

Long distance travel is an unusual activity for humans. The economical cabin environment (low air circulation, limited space, low humidity, etc.) during the long haul flights causes discomfort and even stress for many passengers. In-flight video and music systems are commonly available to improve the comfort level of the passengers. However, current in-flight music systems do not explore how the content can be used to reduce passengers stress. Most of these systems are designed and implemented assuming a homogeneous passenger group that has similar tastes and desires. In this paper, we present a heart rate controlled in-flight music recommendation system for reducing the stress during air travel. The system recommends personalized music playlists to the passengers and attempts to keep their heart rate in a normal range with these playlists. Experiments in a simulated long haul flight cabin environment find that the passengers’ stress can indeed be significantly reduced through listening to the recommended music playlists.

The Effect of Indian Classical Music on Migraine Episodes in Young Females of Age Group 18 to 23 Years

Music has been known for its soothing effects since ancient times. The purpose of this study was to assess the effects of Indian classical music during migraine episodes in young (18 to 23 years) female patients. A standard music playlist was prepared and distributed to the test group of 25 patients. They listened to the music during every migraine attack occurring for a period of 4 months. Questionnaires containing pain scales were administered at 0 month, 2 month and 4 month. The statistical analysis of the responses provided by the patients of the 2 groups (A and B) showed significant differences. The pain intensity during an attack, the duration of an attack and frequency of attacks showed significant decline while alertness after an attack showed considerable improvement in the music group (Group A) subjects. However, subjects of Group B, our non music group, showed no improvement in their migraine symptoms with respect to pain intensity, duration, alertness and frequency of attacks. Our results demonstrate the potential role of Indian classic music as an adjuvant therapy for management of migraine episodes.

An Automated Music Selector Derived from Weather Condition and its Impact on Human Psychology

AbstractSometimes it is disquieting to generate a playlist to listen music for a specific moment. Though listening of music basically depends on our mood and it’s also been said that there exists a relation between our mood and weather, so our approach is to build an automated system to create a music playlist based on users mood and defined weather. Method is to measure the weight of each music files respect to defined mood and weather by using data mining algorithms.

Urban Headphone Listening and the Situational Fit of Music, Radio and Podcasting

Many people wear headphones during movement through their city, and they listen to a variety of sound genres like music, talk, lectures, etc. This study focuses on the pedestrian headphone listener who may spend an hour or more traveling every day. It explores the situational fit of three media; music playlists, live radio, and podcasting, during public transit.A field trial was conducted in London, UK in December 2013. Ten adult iPhone users were exposed to a music playlist on Spotify, live news from London's Biggest Conversation (LBC), and educational podcasts from BBC Radio 4, while simultaneously going about their business in Central London. This study discovered informants were more interested in curating their music, and less interested in engaging with the social concerns of live radio, or the learned address of educational podcasting. Music was felt as relaxing while radio and podcasting were felt as more imposing on their concentration. In sum, the participants found radio and podcasting to have weaker situational fit than music during pedestrian headphone listening.

Synchronized personalized music audio-playlists to improve adherence to physical activity among patients participating in a structured exercise program: a proof-of-principle feasibility study.

BackgroundPreference-based tempo-pace synchronized music has been shown to reduce perceived physical activity exertion and improve exercise performance. The extent to which such strategies can improve adherence to physical activity remains unknown. The objective of the study is to explore the feasibility and efficacy of tempo-pace synchronized preference-based music audio-playlists on adherence to physical activity among cardiovascular disease patients participating in a cardiac rehabilitation.MethodsThirty-four cardiac rehabilitation patients were randomly allocated to one of two strategies: (1) no music usual-care control and (2) tempo-pace synchronized audio-devices with personalized music playlists + usual-care. All songs uploaded onto audio-playlist devices took into account patient personal music genre and artist preferences. However, actual song selection was restricted to music whose tempos approximated patients’ prescribed exercise walking/running pace (steps per minute) to achieve tempo-pace synchrony. Patients allocated to audio-music playlists underwent further randomization in which half of the patients received songs that were sonically enhanced with rhythmic auditory stimulation (RAS) to accentuate tempo-pace synchrony, whereas the other half did not. RAS was achieved through blinded rhythmic sonic-enhancements undertaken manually to songs within individuals’ music playlists. The primary outcome consisted of the weekly volume of physical activity undertaken over 3 months as determined by tri-axial accelerometers. Statistical methods employed an intention to treat and repeated-measures design.ResultsPatients randomized to personalized audio-playlists with tempo-pace synchrony achieved higher weekly volumes of physical activity than did their non-music usual-care comparators (475.6 min vs. 370.2 min, P < 0.001). Improvements in weekly physical activity volumes among audio-playlist recipients were driven by those randomized to the RAS group which attained weekly exercise volumes that were nearly twofold greater than either of the two other groups (average weekly minutes of physical activity of 631.3 min vs. 320 min vs. 370.2 min, personalized audio-playlists with RAS vs. personalized audio-playlists without RAS vs. non-music usual-care controls, respectively, P < 0.001). Patients randomized to music with RAS utilized their audio-playlist devices more frequently than did non-RAS music counterparts (P < 0.001).ConclusionsThe use of tempo-pace synchronized preference-based audio-playlists was feasibly implemented into a structured exercise program and efficacious in improving adherence to physical activity beyond the evidence-based non-music usual standard of care. Larger clinical trials are required to validate these findings.Trial registrationClinicalTrials.gov ID (NCT01752595)Electronic supplementary materialThe online version of this article (doi:10.1186/s40798-015-0017-9) contains supplementary material, which is available to authorized users.

Playlist for the Dead by Michelle Falkoff (review)

Reviewed by: Playlist for the Dead by Michelle Falkoff Deborah Stevenson, Editor Falkoff, Michelle Playlist for the Dead. HarperTeen/HarperCollins, 2015 [288p] Trade ed. ISBN 978-0-06-231050-7 $17.99 E-book ed. ISBN 978-0-06-231052-1 $10.99 Reviewed from galleys R Gr. 8-10 Sam knew that his best friend, Hayden, had a lot going wrong in his life, especially savage bullying at the hands of his brother and his brother’s best friends, but Sam’s still stunned when Hayden commits suicide. Now sixteen-year-old Sam is trying to unpack the story of what pushed Hayden over the edge—and to figure out how much is his fault. He tries to decipher the music playlist Hayden left him and find out more backstory from Hayden’s computer; he also connects with an intriguing girl, Astrid, who’s gratifyingly interested in the romantically inexperienced Sam, but who also has information about Hayden she’s keeping from him. The “finding truth behind the suicide” plot isn’t new, but Falkoff offers a more dimensional take than many, as Sam begins to realize how much more is going on in everybody’s life than he perceived. That realization comes both from finding a web of acquaintances that Sam had no idea Hayden had and also from discovering that people he might have dismissed (including, in a solid supporting role, his sister’s body-modded new boyfriend) are actually worth knowing. There’s more than a bit of mystery to the layers beyond who did what, who failed Hayden and how, and who’s currently taking revenge on the “bully trifecta,” adding further interest to an already compelling tale. Provocative ethical questions and considerable emotional impact will make this a lively book for discussion as well as an absorbing and sensitive read. Copyright © 2015 The Board of Trustees of the University of Illinois

‘Four Seasons’ in an animal rescue centre; classical music reduces environmental stress in kennelled dogs

On admission to rescue and rehoming centres dogs are faced with a variety of short- and long-term stressors including novelty, spatial/social restriction and increased noise levels. Animate and inanimate environmental enrichment techniques have been employed within the kennel environment in an attempt to minimise stress experienced by dogs. Previous studies have shown the potential physiological and psychological benefits of auditory stimulation, particularly classical music, within the kennel environment. This study determined the physiological/psychological changes that occur when kennelled dogs are exposed to long-term (7days) auditory stimulation in the form of classical music through assessment of effects on heart rate variability (HRV), salivary cortisol and behaviour. The study utilised a cross over design in which two groups were exposed to two consecutive 7day treatments; silence (control) and classical music (test). Group A was studied under silent conditions followed by 7days of test conditions during which a fixed classical music playlist was played from 10:00–16:30h. Group B received treatment in the reverse order. Results showed that auditory stimulation induced changes in HRV and behavioural data indicative of reduced stress levels in dogs in both groups (salivary cortisol data did not show any consistent patterns of change throughout the study). Specifically, there was a significant increase in HRV parameters such as μRR, STDRR, RMSSD, pNN50, RRTI, SD1 and SD2 and a significant decrease in μHR and LF/HF from the first day of silence (S1) to the first day of music (M1). Similarly, examination of behavioural data showed that dogs in both groups spent significantly more time sitting/lying and silent and less time standing and barking during auditory stimulation. General Regression Analysis (GRA) of the change in HRV parameters from S1 to M1 revealed that male dogs responded better to auditory stimulation relative to female. Interestingly, HRV and behavioural data collected on the seventh day of music (M2) was similar to that collected on S1 suggesting that the calming effects of music are lost within the 7days of exposure. A small ‘9-Day’ study was conducted in attempt to determine the time-scale in which dogs become habituated to classical music and examination of the results suggests that this occurs within as soon as the second day of exposure. The results of this study show the potential of auditory stimulation as a highly effective environmental enrichment technique for kennelled dogs. However, the results also indicate the requirement for further investigations into the way in which auditory stimulation should be incorporated within the daily kennel management regime in order to harness the full physiological and psychological benefits of music.

From mixtapes to multiplayers: Sharing musical taste through video games

Abstract In the late twentieth century, the mixtape was a popular way in which fans shared their taste in music with others in their social network; the author of a mixtape would record a compilation of music, often an assortment of works by various artists, onto an audio cassette, and presented this playlist as a curated, thematic listening experience for the recipient of the mixtape. Since then, the mixtape has moved beyond tangible recording media to online peer-to-peer file sharing services (such as Napster) and shared, user-curated playlists on commercial music streaming services such as Spotify. In recent years, these playlists have been gamified – elements of competition, achievement and self-expression have been added to curated listening experiences in games wherein players create in-game musical playlists, share these playlists with others, challenge other players to quiz games about songs in their favourite genre, etc. Viewing social video games as transmutations of the mixtape, the article focuses on ways in which these games are emerging as vehicles of self-expression and taste sharing by examining the various degrees and methods of curatorial control afforded to players (and game creators) regarding the selection and sharing of musical content in gameplay and extending into ‘real life’.

Quantifying auditory temporal stability in a large database of recorded music.

“Moving to the beat” is both one of the most basic and one of the most profound means by which humans (and a few other species) interact with music. Computer algorithms that detect the precise temporal location of beats (i.e., pulses of musical “energy”) in recorded music have important practical applications, such as the creation of playlists with a particular tempo for rehabilitation (e.g., rhythmic gait training), exercise (e.g., jogging), or entertainment (e.g., continuous dance mixes). Although several such algorithms return simple point estimates of an audio file’s temporal structure (e.g., “average tempo”, “time signature”), none has sought to quantify the temporal stability of a series of detected beats. Such a method-a “Balanced Evaluation of Auditory Temporal Stability” (BEATS)–is proposed here, and is illustrated using the Million Song Dataset (a collection of audio features and music metadata for nearly one million audio files). A publically accessible web interface is also presented, which combines the thresholdable statistics of BEATS with queryable metadata terms, fostering potential avenues of research and facilitating the creation of highly personalized music playlists for clinical or recreational applications.

Automated Generation of Music Playlists: Survey and Experiments

Most of the time when we listen to music on the radio or on our portable devices, the order in which the tracks are played is governed by so-called playlists. These playlists are basically sequences of tracks that traditionally are designed manually and whose organization is based on some underlying logic or theme. With the digitalization of music and the availability of various types of additional track-related information on the Web, new opportunities have emerged on how to automate the playlist creation process. Correspondingly, a number of proposals for automated playlist generation have been made in the literature during the past decade. These approaches vary both with respect to which kind of data they rely on and which types of algorithms they use. In this article, we review the literature on automated playlist generation and categorize the existing approaches. Furthermore, we discuss the evaluation designs that are used today in research to assess the quality of the generated playlists. Finally, we report the results of a comparative evaluation of typical playlist generation schemes based on historical data. Our results show that track and artist popularity can play a dominant role and that additional measures are required to better characterize and compare the quality of automatically generated playlists.

An Accurate Algorithm for Generating a Music Playlist based on Facial Expressions

Manual segregation of a playlist and annotation of songs, in accordance with the current emotional state of a user, is labor intensive and time consuming. Numerous algorithms have been proposed to automate this process. However the existing algorithms are slow, increase the overall cost of the system by using additional hardware (e.g. EEG systems and sensors) and have less accuracy. This paper presents an algorithm that automates the process of generating an audio playlist, based on the facial expressions of a user, for rendering salvage of time and labor, invested in performing the process manually. The algorithm proposed in this paper aspires to reduce the overall computational time and the cost of the designed system. It also aims at increasing the accuracy of the designed system. The facial expression recognition module of the proposed algorithm is validated by testing the system against user dependent and user independent dataset. Experimental results indicate that the user dependent results give 100% accuracy, while user independent results for joy and surprise are 100 %, but for sad, anger and fear are 84.3 %, 80 % and is 66% respectively. The overall accuracy of the emotion recognition algorithm, for user independent dataset is 86%. In audio, 100 % recognition rates are obtained for sad, sad-anger and joy-anger but for joy and anger, recognition rates obtained are 95.4% and 90 % respectively. The overall accuracy of the audio emotion recognition algorithm is 98%. Implementation and testing of the proposed algorithm is carried out using an inbuilt camera. Hence, the proposed algorithm reduces the overall cost of the system successfully. Also, on average, the proposed algorithm takes 1.10 sec to generate a playlist based on facial expression. Thus, it yields better performance, in terms of computational time, as compared to the algorithms in the existing literature.

Music Playlist Tempo And Self-Paced Running, Mood, And Attentional Focus

Music Playlist Tempo And Self-Paced Running, Mood, And Attentional Focus

Listening to Music and Active Music Therapy in Behavioral Disturbances in Dementia: A Crossover Study

Listening to Music and Active Music Therapy in Behavioral Disturbances in Dementia: A Crossover Study

Digital Music Exposure Reliably Induces Temporary Threshold Shift in Normal-Hearing Human Subjects

One of the challenges for evaluating new otoprotective agents for potential benefit in human populations is the availability of an established clinical paradigm with real-world relevance. These studies were explicitly designed to develop a real-world digital music exposure that reliably induces temporary threshold shift (TTS) in normal-hearing human subjects. Thirty-three subjects participated in studies that measured effects of digital music player use on hearing. Subjects selected either rock or pop music, which was then presented at 93 to 95 (n = 10), 98 to 100 (n = 11), or 100 to 102 (n = 12) dBA in-ear exposure level for a period of 4 hr. Audiograms and distortion product otoacoustic emissions (DPOAEs) were measured before and after music exposure. Postmusic tests were initiated 15 min, 1 hr 15 min, 2 hr 15 min, and 3 hr 15 min after the exposure ended. Additional tests were conducted the following day and 1 week later. Changes in thresholds after the lowest-level exposure were difficult to distinguish from test-retest variability; however, TTS was reliably detected after higher levels of sound exposure. Changes in audiometric thresholds had a "notch" configuration, with the largest changes observed at 4 kHz (mean = 6.3 ± 3.9 dB; range = 0-14 dB). Recovery was largely complete within the first 4 hr postexposure, and all subjects showed complete recovery of both thresholds and DPOAE measures when tested 1 week postexposure. These data provide insight into the variability of TTS induced by music-player use in a healthy, normal-hearing, young adult population, with music playlist, level, and duration carefully controlled. These data confirm the likelihood of temporary changes in auditory function after digital music-player use. Such data are essential for the development of a human clinical trial protocol that provides a highly powered design for evaluating novel therapeutics in human clinical trials. Care must be taken to fully inform potential subjects in future TTS studies, including protective agent evaluations, that some noise exposures have resulted in neural degeneration in animal models, even when both audiometric thresholds and DPOAE levels returned to pre-exposure values.

If You Like Radiohead, You Might Like This Article

With the recent dramatic transformations in the world of digital music, a music listener is now just a couple of clicks away from being able to listen to nearly any song that has ever been recorded. With so much music readily available, tools that help a user find new, interesting music that matches his or her taste become increasingly important. In this article we explore one such tool: music recommendation. We describe common music recommendation use cases such as finding new artists, finding others with similar listening tastes, and generating interesting music playlists. We describe the various approaches currently being explored by practitioners to satisfy these use cases. Finally, we show how results of three different music recommendation technologies compare when applied to the task of finding similar artists to a seed artist.

A multicriteria ant colony algorithm for generating music playlists

In this paper we address the problem of music playlist generation based on the user-personalized specification of context information. We propose a generic semantic multicriteria ant colony algorithm capable of dealing with domain-specific problems by the use of ontologies. It also employs any associated metadata defined in the search space to feed its solution-building process and considers any restrictions the user may have specified. An example is given of the use of the algorithm for the problem of automatic generation of music playlists, some experimental results are presented and the behavior of the approach is explained in different situations.

An Auditory Display in Playlist Generation

A current area of research within music information retrieval is the automatic formation of music playlists: automatically creating a meaningful arrangement of music tracks. It is an application area particularly suited for accessing music on mobile devices as music collections are becoming too large to manually navigate. The growth of music streaming services means that even more vast collections of music are accessible from a mobile device. Much energy has been spent constructing the best algorithms to create a playlist, but less has been spent on how that algorithm is presented and accessed, particularly on a mobile device.

The Effects of Music as Therapy on the Overall Well-Being of Elderly Patients on Maintenance Hemodialysis

In this study, the authors explored the use of music during hemodialysis (HD) as a complementary therapy to improve overall well-being in elderly patients. The authors recruited a convenience sample of 88 patients on maintenance HD from a teaching hospital in northern Taiwan and randomly assigned them to either an experimental group (n = 44) or a control group (n = 44). In the first week, participants in the experimental group created their own music playlists. During the second week, these participants listened to music from their own playlists during each HD session (three times/week). The authors evaluated the effects of music as therapy by assessing its impact on perceived stressors and adverse reactions during HD (HD Adverse Reactions Self-Assessment Scale and HD Stressor Scale [HSS]) and measuring changes in physiological indices during the course of the music listening. After 1 week of the use of music as therapy during HD, the authors noted significant reductions in the frequency and severity of adverse reactions during dialysis and in scores on the HSS, p < .001. The authors also observed significantly decreased respiratory rate and significantly increased finger temperature and oxygen saturation, p < .001, during the same period. In conclusion, listening to music during HD may promote overall patient well-being. It may thus serve as a complementary form of therapy that facilitates care and delivery of adequate dialysis and thus improves overall patient well-being in the long run.

Piece wise Laplacian‐based Projection for Interactive Data Exploration and Organization

AbstractMultidimensional projection has emerged as an important visualization tool in applications involving the visual analysis of high‐dimensional data. However, high precision projection methods are either computationally expensive or not flexible enough to enable feedback from user interaction into the projection process. A built‐in mechanism that dynamically adapts the projection based on direct user intervention would make the technique more useful for a larger range of applications and data sets. In this paper we propose the Piecewise Laplacian‐based Projection (PLP), a novel multidimensional projection technique, that, due to the local nature of its formulation, enables a versatile mechanism to interact with projected data and to allow interactive changes to alter the projection map dynamically, a capability unique of this technique. We exploit the flexibility provided by PLP in two interactive projection‐based applications, one designed to organize pictures visually and another to build music playlists. These applications illustrate the usefulness of PLP in handling high‐dimensional data in a flexible and highly visual way. We also compare PLP with the currently most promising projections in terms of precision and speed, showing that it performs very well also according to these quality criteria.

Modelling and learning user preferences over sets

Although there has been significant research on modelling and learning user preferences for various types of objects, there has been relatively little work on the problem of representing and learning preferences over sets of objects. We introduce a representation language, DD-PREF, that balances preferences for particular objects with preferences about the properties of the set. Specifically, we focus on the depth of objects (i.e. preferences for specific attribute values over others) and on the diversity of sets (i.e. preferences for broad vs. narrow distributions of attribute values). The DD-PREF framework is general and can incorporate additional object- and set-based preferences. We describe a greedy algorithm, DD-Select, for selecting satisfying sets from a collection of new objects, given a preference in this language. We show how preferences represented in DD-PREF can be learned from training data. Experimental results are given for three domains: a blocks world domain with several different task-based preferences, a real-world music playlist collection, and rover image data gathered in desert training exercises.