Feature Selection Approaches for Optimising Music Emotion Recognition Methods

The high feature dimensionality is a challenge in music emotion recognition. There is no common consensus on a relation between audio features and emotion. The MER system uses all available features to recognize emotion; however, this is not an optimal solution since it contains irrelevant data acting as noise. In this paper, we introduce a feature selection approach to eliminate redundant features for MER. We created a Selected Feature Set (SFS) based on the feature selection algorithm (FSA) and benchmarked it by training with two models, Support Vector Regression (SVR) and Random Forest (RF) and comparing them against with using the Complete Feature Set (CFS). The result indicates that the performance of MER has improved for both Random Forest (RF) and Support Vector Regression (SVR) models by using SFS. We found using FSA can improve performance in all scenarios, and it has potential benefits for model efficiency and stability for MER task

The curious case of the refrigerator-TV: similarity and hybridization

This paper examines the role of similarity in the hybridization of concepts, focusing on hybrid products as an applied test case. Hybrid concepts found in natural language, such as singer songwriter, typically combine similar concepts, whereas dissimilar concepts rarely form hybrids. The hybridization of dissimilar concepts in products such as jogging shoe mp3 player, and refrigerator TV thus poses a challenge for understanding the process of conceptual combination. It is proposed that models of conceptual combination can throw light on the judged future success and desirability of hybrid products in general. The composite prototype model proposes two stages of conceptual combination. In the first stage, the concepts are aggregated into an additive hybrid, simply by forming the union of the two sets of attributes. In the second stage, any conflicting attributes are identified and resolved, often with the introduction of emergent attributes, resulting in an integrative hybrid. Across four studies that varied the similarity and type of hybrid products, similar and integrative hybrids were valued more than dissimilar and additive hybrids. Critically, though, dissimilar hybrids were also highly valued if they were integrative. Results supported the two stages proposed by the composite prototype model, and implications for other models of hybrid formation are discussed

The Appreciative Heart: The Psychophysiology of Positive Emotions and Optimal Functioning

This monograph is an overview of Institute of HeartMath's research on the physiological correlates of positive emotions and the science underlying two core HeartMath techniques which supports Heart-Based Living. The heart's connection with love and other positive emotions has survived throughout millennia and across many diverse cultures. New empirical research is providing scientific validation for this age-old association. This 21-page monograph offers a comprehensive understanding of the Institute of HeartMath's cutting-edge research exploring the heart's central role in emotional experience. Described in detail is physiological coherence, a distinct mode of physiological functioning, which is generated during sustained positive emotions and linked with beneficial health and performance-related outcomes. The monograph also provides steps and applications of two HeartMath techniques, Freeze-Frame(R) and Heart Lock-In(R), which engage the heart to help transform stress and produce sustained states of coherence. Data from outcome studies are presented, which suggest that these techniques facilitate a beneficial repatterning process at the mental, emotional and physiological levels

Temporal Awareness and Rhythmic Performance

The objective of this research was to study the conditions under which rhythmic behavior arises and its effects on task performance and mental workload. It has been demonstrated that temporal awareness (TA) in dynamic systems draws on high-level mental resources and contributes to superior performance on some task elements but not others. Elsewhere it has been demonstrated that TA in environments with high predictability can lead to superior task performance and reduced mental workload. This research sought to examine the behavior and subsequent performance that arises under highly predictable vs. dynamic conditions. Using a computer-based time-sharing task, we analyzed task performance and temporal awareness under 3 levels of rhythm (easy, difficult, and arrhythmic) and 2 levels of response task difficulty. Results indicate that rhythmic presentation of both response task levels leads to reduced levels of mental workload, but offers no discernible benefits to task performance. Participants exhibited greater TA in rhythmic conditions as compared to arrhythmic conditions. Further testing with more realistic response tasks and a greater balance in rhythm levels is needed to more accurately describe participants\u27 subjective experience of rhythm and its effects on task performance

Influence of Self-regulation and Motivational Beliefs on University Music Students\u27 Use of Practice Strategies

The purpose of this study was to determine whether there is a relationship between university music students\u27 self-regulation, motivational beliefs, and background characteristics and the number and kinds of practice strategies used during 30 min of practicing. The research questions used to guide this study were: After controlling for participants\u27 known background characteristics (age, sex, primary instrument, years of playing, years of private lessons, average hr of practice per week, and training on another instrument), do university music students\u27 self-regulatory abilities, self-perceptions and motivational beliefs (self-efficacy, locus of causal attributions, goal orientation, and implicit talent beliefs) predict the number of practice strategies used during a 30-min practice session? and After controlling for participants\u27 known background characteristics (age, sex, primary instrument, years of playing, years of private lessons, average hr of practice per week, and training on another instrument), do university music students\u27 self-regulatory abilities, self-perceptions and motivational beliefs (self-efficacy, locus of causal attributions, goal orientation, and implicit talent beliefs) predict the total kinds of practice strategies used during a 30-min practice session? Participants in this study were undergraduate music students who played woodwind (n = 20) or brass instruments (n = 20), from three different universities in the mid-South. Results from a multiple regression revealed that participants\u27 self-regulation, self-efficacy, locus of causal attributions, goal orientations, implicit talent beliefs, and background characteristics accounted for 56% of the outcome variable total number of strategies used. The strongest predictor that contributed to the regression model was performance approach goal orientation (ß = .57), followed by sex (ß = .52), locus of causal attributions (ß = -.52), and self-regulation (ß = .38). Results from the second multiple regression revealed that participants\u27 self-regulation, self-efficacy, locus of causal attributions, goal orientations, implicit talent beliefs, and background characteristics accounted for 53% of the outcome variable kinds of strategies used. The strongest predictor that contributed to the regression model was the performance avoid goal orientation (ß = .42), followed by primary instrument family (ß = .37), self-efficacy (ß = -.30),self-regulation (ß = .29), and sex (ß = .29). Future research and implications for music educators are discussed

Cantus: Construction and evaluation of a software solution for real-time vocal music training and musical intonation assessment

The development of the ability to sing or play in tune is one of the most critical tasks in music training. In music education, melodic patterns are usually learned by imitative processes (modelling). Once modelled, pitch sounds are then associ-ated to a representation according to a syllabic system such as the Guidonian system - or an arbitrary single syllable - or western graphic notation system symbols. From a didactic standpoint, few advances have been made in this area besides the use of audio-supported guides and existing software, which use a microphone to analyse the input and estimate the pitch or fundamental frequency of the given tone. However, these programmes lack the necessary analytical algo-rithm to provide the student with precise feedback on their execution; and also they do not provide adequate noise-robust solutions to minimize the student assessment error rate. The ongoing research discussed in this article focuses on Cantus, a new software solution expressly designed as an assessment and diagnosis tool for online training and assessment of vocal musical intonation at the initial stages of music education. Cantus software embodies the latest research on real-time analy-sis of audio stream, which permits the teacher to customize music training by means of recording patterns and embedding them into the programme. The study presented in this article includes the design, implementation and assessment of Cantus by music teachers. The pilot study for the software assessment includes a sample of 21 music teachers working at thirteen music schools in Valencia, Spain. These teachers worked with the software at their own pace for a week in order to evaluate it. Subsequently, a two-part questionnaire was filled in with (1) ques-tions related to demographics, professional experience and the use of ITC; and (2) questions related to the software's technical and didactic aspects. The question-naire also included three open questions related to Cantus, namely advantages, issues and suggestions. The results show an excellent reception by teachers, who consider this software as a highly adequate music training tool at the initial stages of music education