Investigating the influence of music training on verbal memory

Previous research has shown that musical training is associated with enhanced verbal memory. The current study investigated the generality of this association by presenting undergraduates who had received musical training (n = 20) and undergraduates with no formal music training (n = 20) with four types of word list; high visual imagery, high auditory imagery, high tactile imagery, and abstract. Those who had received music training showed enhanced memory for all word lists, suggesting that music training leads to a general enhancement in verbal memory that is not restricted to specific types of words (e.g., those invoking auditory imagery). The findings support previous research in showing that music training enhances cognitive skills beyond those that are specific to the domain of music. The possible cognitive and neural factors underpinning this effect are discussed

Short-Term Orchestral Music Training Modulates Hyperactivity and Inhibitory Control in School-Age Children: A Longitudinal Behavioural Study

Survey studies have shown that participating in music groups produces several benefits, such as discipline, cooperation and responsibility. Accordingly, recent longitudinal studies showed that orchestral music training has a positive impact on inhibitory control in school-age children. However, most of these studies examined long periods of training not always feasible for all families and institutions and focused on children’s measures ignoring the viewpoint of the teachers. Considering the crucial role of inhibitory control on hyperactivity, inattention and impulsivity, we wanted to explore if short orchestral music training would promote a reduction of these impulsive behaviors in children. This study involved 113 Italian children from 8 to 10 years of age. 55 of them attended 3 months of orchestral music training. The training included a 2-hour lesson per week at school and a final concert. The 58 children in the control group did not have any orchestral music training. All children were administered tests and questionnaires measuring inhibitory control and hyperactivity near the beginning and end of the 3-month training period. We also collected information regarding the levels of hyperactivity of the children as perceived by the teachers at both time points. Children in the music group showed a significant improvement in inhibitory control. Moreover, in the second measurement the control group showed an increase in self-reported hyperactivity that was not found in the group undergoing the music training program. This change was not noticed by the teachers, implying a discrepancy between self-reported and observed behavior at school. Our results suggest that even an intense and brief period of orchestral music training is sufficient to facilitate the development of inhibitory control by modulating the levels of self-reported hyperactivity. This research has implications for music pedagogy and education especially in children with high hyperactivity. Future investigations will test whether the findings can be extended to children diagnosed with ADHD

Learning about what constitutes effective training from a pilot programme to improve music education in primary schools

The new primary strategy in England raised the profile of foundation subjects, including music, yet many primary school teachers lack skills and confidence in their ability to teach music. This research explores a year-long programme of training across 16 primary schools in England that sought to improve music education. The programme involved whole school in-service training, advisory teachers offering support within the classroom and further training for music co-ordinators. The implementation of the programme, the training received, lesson observations throughout the programme, difficulties arising and the longer term benefits were explored through questionnaires, interviews and school visits with participant teachers, and senior managers in the Local Authorities and schools. The findings indicated that the programme had been effective in improving teacher confidence, and musical understanding, and the quality of teaching. Factors contributing to the success of the programme were identified and lessons for the development and implementation of future programmes

The psychological, psychophysical and ergogenic effects of music in sport: A review and synthesis

This is the post-print of this chapter - Copyright @ 2008 RoutledgeWe have presented two complementary conceptual approaches underlying the study and application of music in sport and exercise contexts [103, 104]. We have also established that music can be applied to sports training and competition in many different ways, and have provided 573 initial evidence for a quartic relationship between exercise heart rate and music tempo preference. One of the main demonstrated benefits of music is that it enhances psychological state, which has implications for optimising pre-competition mental state and increasing the enjoyment of training activities. Used synchronously, music can boost work output and makes repetitive tasks such as cycling or running more energy efficient. When we embarked upon our programme of research almost two decades ago, our intention was to promote more judicious use of music. The evidence that we have accumulated coupled with the findings of many other researchers from around the world, should allow athletes and practitioners to tap the psychological, psychophysical and ergogenic effects of music with greater precision

Philosophy of Music Education

A philosophy of music education refers to the value of music, the value of teaching music, and how to practically utilize those values in the music classroom. This thesis explores the philosophies of Emile Jacques-Dalcroze, Carl Orff, Zoltan Kodaly, Bennett Reimer, and David Elliott, and suggests practical applications or their philosophies in the orchestral classroom, especially in the context of ear training and improvisation. From these philosophies, the author develops their own personal philosophy of music education, most broadly defined by the claim that music is key to experiencing and understanding feelingful experiences

Transfer learning by supervised pre-training for audio-based music classification

Very few large-scale music research datasets are publicly available. There is an increasing need for such datasets, because the shift from physical to digital distribution in the music industry has given the listener access to a large body of music, which needs to be cataloged efficiently and be easily browsable. Additionally, deep learning and feature learning techniques are becoming increasingly popular for music information retrieval applications, and they typically require large amounts of training data to work well. In this paper, we propose to exploit an available large-scale music dataset, the Million Song Dataset (MSD), for classification tasks on other datasets, by reusing models trained on the MSD for feature extraction. This transfer learning approach, which we refer to as supervised pre-training, was previously shown to be very effective for computer vision problems. We show that features learned from MSD audio fragments in a supervised manner, using tag labels and user listening data, consistently outperform features learned in an unsupervised manner in this setting, provided that the learned feature extractor is of limited complexity. We evaluate our approach on the GTZAN, 1517-Artists, Unique and Magnatagatune datasets

EMIR: A novel emotion-based music retrieval system

Music is inherently expressive of emotion meaning and affects the mood of people. In this paper, we present a novel EMIR (Emotional Music Information Retrieval) System that uses latent emotion elements both in music and non-descriptive queries (NDQs) to detect implicit emotional association between users and music to enhance Music Information Retrieval (MIR). We try to understand the latent emotional intent of queries via machine learning for emotion classification and compare the performance of emotion detection approaches on different feature sets. For this purpose, we extract music emotion features from lyrics and social tags crawled from the Internet, label some for training and model them in high-dimensional emotion space and recognize latent emotion of users by query emotion analysis. The similarity between queries and music is computed by verified BM25 model

Neural Audio: Music Information Retrieval Using Deep Neural Networks

The use of deep neural networks has exploded in popularity recently. Thinking that music information retrieval should not be left out of this trend in machine learning, we explore two different applications of this technology in the field. The first we looked at was genre identificaton, using the initial categories of \u27popular music,\u27 \u27art music,\u27 and \u27traditional music.\u27 This was found to be a difficult problem - classifying music into these categories can be challenging even for experts, and assembling a large dataset for use in training represents a significant problem. The second approach we took to using these techniques was looking at instrument identification, specifically for the purpose of identifying the time and category (from guitar, vocal, or drum ) of solos in popular music