Ensemble Performance Research Articles

НЕКОТОРЫЕ ОСОБЕННОСТИ СОВРЕМЕННОГО АНСАМБЛЕВОГО ИСПОЛНИТЕЛЬСТВА В КУРСЕ ОБЩЕГО ФОРТЕПИАНО

The article deals with the peculiarities of modern piano ensemble performance in the pedagogical activity of a higher school teacher. The influence of ensemble music-making on the development of the professional skills and personal qualities of students of various specialties is emphasized. Due to the modern Russian education modernization, and on the basis of long-term pedagogical experience and extensive concert activity, the author provides recommendations on working with students of various specialties in the general piano course aimed at developing interaction, improving the quality of sound and fundamental music erudition.

Psychological benefits of networking technologies in children’s experience of ensemble music making

Little is currently known about the possible benefits of using networked technology to enhance ensemble performance. This study explored whether the introduction of specially devised technology – networked tablets using traditional music notation – to a primary school orchestra would enhance the experience of ensemble music. Particular emphasis was placed on how the technology could help children to overcome practical problems associated with ensemble playing for early-stage musicians (e.g., keeping in sync with other players), thereby leading to better engagement with the music and ultimately greater enjoyment. Findings from a thematic analysis of responses from a focus group with eight young orchestra players aged 9–11 years and from an interview with the orchestra conductor, together with indications from the statistical analysis of 28 orchestra participants’ questionnaire responses, suggest that the technology did help to reduce the practical problems associated with ensemble playing. This appeared to interrupt the downward spiral of frustration and lack of confidence in playing for some young people, and enhanced the likelihood of feelings of enjoyment and belonging.

Introduction to the special issue on “25 years of ensemble forecasting”

Twenty‐five years ago the first operational, ensemble forecasts were issued by the European Centre for Medium‐Range Weather Forecasts and the National Centers for Environmental Prediction. These centres were followed in 1996 by the Meteorological Service of Canada, and in the subsequent years by many others. Operational ensemble‐based, probabilistic forecasts signed a paradigm shift in weather prediction: for the first time, forecasters and users could have reliable and accurate estimates of the range of possible future scenarios, and not just a single realization of the future. Today, ensembles are used not only to provide reliable and accurate forecasts for the short and medium range, the monthly and seasonal time‐scale, but also to provide estimates of the initial state of the atmosphere, and to generate future climate projections. This article provides an overview on how we developed the early ensembles, illustrates the key characteristics of the seven operational, global, medium‐range ensembles, and discusses ongoing trends to further improve ensemble performance.

An Analysis of Ratings and Interrater Reliability of Adjudicated Orchestra Festivals

Abstract The purpose of this study was to identify the influence of school level (middle and high), festival level (district and state), music classification (A, B, C, D, and E), and instrumentation (full and string orchestra) on the overall performance ratings assigned to orchestral performances at large ensemble Music Performance Assessment (MPA) festivals. Data consisted of overall ratings (N = 1,996) assigned at district (n = 1,844) and state level (n = 152) MPA festivals sponsored by the Florida Orchestra Association between 2010 and 2015. Analysis revealed that 94% of all high school orchestras at district and state festivals earned a I/Superior or II/Excellent rating. Logistic regression models revealed: (a) high school orchestras were more likely to earn I/Superior ratings at district festivals than state festivals, (b) middle school orchestras were less likely to earn I/Superior ratings than high school orchestras, and (c) orchestras that performed more difficult repertoire increased their likelihood of earning a I/Superior over ensembles that played easier literature. Festival administrators may use the results of this study to identify specific evaluation trends at adjudicated festivals that can be strengthened.

Software Defect Prediction Using Ensemble Learning: An ANP Based Evaluation Method

Software defect prediction (SDP) is the process of predicting defects in software modules, it identifies the modules that are defective and require extensive testing. Classification algorithms that help to predict software defects play a major role in software engineering process. Some studies have depicted that the use of ensembles is often more accurate than using single classifiers. However, variations exist from studies, which posited that the efficiency of learning algorithms might vary using different performance measures. This is because most studies on SDP consider the accuracy of the model or classifier above other performance metrics. This paper evaluated the performance of single classifiers (SMO, MLP, kNN and Decision Tree) and ensembles (Bagging, Boosting, Stacking and Voting) in SDP considering major performance metrics using Analytic Network Process (ANP) multi-criteria decision method. The experiment was based on 11 performance metrics over 11 software defect datasets. Boosted SMO, Voting and Stacking Ensemble methods ranked highest with a priority level of 0.0493, 0.0493 and 0.0445 respectively. Decision tree ranked highest in single classifiers with 0.0410. These clearly show that ensemble methods can give better classification results in SDP and Boosting method gave the best result. In essence, it is valid to say that before deciding which model or classifier is better for software defect prediction, all performance metrics should be considered.Keywords— Data mining, Machine Learning, Multi Criteria Decision Making, Software Defect Prediction

V. Telychko’s “Children’s Album” as an example of the modern tonal image of the world: peculiarities of the musical vocabulary and melodic ideas.

V. Telychko’s “Children’s Album” as an example of the modern tonal image of the world: peculiarities of the musical vocabulary and melodic ideas.

V. Telychko’s “Children’s Album” as an example of the modern tonal image of the world: peculiarities of the musical vocabulary and melodic ideas.

V. Telychko’s “Children’s Album” as an example of the modern tonal image of the world: peculiarities of the musical vocabulary and melodic ideas.

Temporal issues in the inherent rhythmic expressions of African indigenous music performance practices

This study focused on the reception and interpretation of African rhythmic expression and the management of independent roles in ensemble performance practices. Two points of view were explicitly discussed in this work to reveal the significance of cultural background in the reception and interpretation of a musical culture. African scholar’s perception and representation of independent rhythmic roles and instrumental blend in an ensemble forms the first view, while the second view is the perception of non-African scholar; their interpretation and representation of individual roles and rhythmic expression of indigenous African musical performance practices. These were examined using indigenous music practices of Igbo ethnicity in Nigeria as sample material. Data collected was through review of related literature, participant observation and personal interview. Finding revealed that the determinant factors for African compositional techniques, temporal application and implication in their performance practices are mere expression of cultural heritage or inherent life style playing out in musical expressions. Thus, the recommendation emphasized that for any scholar to rightly interpret and denote the cultural signifiers in the temporal involvement in African music culture his/her understanding of the people’s cultural principles, myths, connotations, tonal syntax, semantics, semiotics denotations and inter-semiotics is germen.

Improving networked music performance systems using application‐network collaboration

SummaryNetworked Music Performance (NMP) systems involve musicians located in different places who perform music while staying synchronized via the Internet. The maximum end‐to‐end delay in NMP applications is called Ensemble Performance Threshold (EPT) and should be less than 25 milliseconds. Due to this constraint, NMPs require ultra–low‐delay solutions for audio coding, network transmission, relaying, and decoding, each one a challenging task on its own. There are two directions for study in the related work referring to the NMP systems. From the audio perspective, researchers experiment on low‐delay encoders and transmission patterns, aiming to reduce the processing delay of the audio transmission, but they ignore the network performance. On the other hand, network‐oriented researchers try to reduce the network delay, which contributes to reduced end‐to‐end delay. In our proposed approach, we introduce an integration of dynamic audio and network configuration to satisfy the EPT constraint. The basic idea is that, the major components participating in an NMP system, the application and the network interact during the live music performance. As the network delay increases, the network tries to equalize it by modifying the routing behavior using Software‐Defined Networking principles. If the network delay exceeds a maximum affordable threshold, the network reacts by informing the application to change the audio processing pattern to overcome the delay increase, resulting in below EPT end‐to‐end delay. A full prototype of the proposed system was implemented and extensively evaluated in an emulated environment.

Please turn it down!

Sustained levels of 95 to 100 dBA and beyond are not uncommon in rock and pop music genres, leading to daily noise doses that are 100% or more above the recommendations established by the National Institute for Occupational Safety and Health. There are three options of addressing this situation: leaving the environment, using hearing protection, and turning the offending level down. It is the last of these that I will explore. The first two listed have problems with implementation. Using Leq measurements of various ensemble performance situations, the question addressed is whether or not musicians can learn to control the level of their instruments efficiently enough, referencing NIOSH recommended noise exposures, to make a meaningful difference in exposure time without significantly sacrificing the quality of the music.

Large and local-scale features associated with heat waves in the United States in reanalysis products and the NARCCAP model ensemble

This study investigates the role of large-scale and local-scale processes associated with heat waves using two reanalysis products, and evaluates the performance of the regional climate model ensemble used in the North America Regional Climate Change Program (NARCCAP) in reproducing these processes. The Continental US is divided into eight different climate divisions to investigate different mechanisms associated with heat waves. At the large scale, heat waves are associated with terrestrial warm air advection to the Northeast, Midwest and Northern Great Plains, and with oceanic warm air advection for the Southeast and Southern Great Plains. Over the western US, reduced maritime cool air advection results in local warming. At the local scale, antecedent precipitation deficits lead to the continuous drying of soil, more net radiative energy is partitioned into sensible heat flux and acts to warm surface air temperature, especially over the Great Plains. NARCCAP-simulated large-scale meteorological patterns and temporal evolution of antecedent local scale terrestrial conditions are shown to be very similar to those of the reanalysis products. Even though extreme temperature is overestimated by the NARCCAP ensemble over the US, different heat wave metrics are realistically represented both in terms of the inter-annual variability and spatial representation. However, NARCCAP overestimates the magnitude of heatwaves over the Northeast, Midwest and Northern Great Plains, partially due to anomalous heat advection through large-scale forcing.

Simulating evaluation and projection of the climate zones over China by CMIP5 models

On the basis of climate zones classified by the number of days of the daily average temperature ≥ 10 °C (DT10) over China, the performance of the 9 CMIP5 climate models is evaluated in this paper. The results indicate that the CMCC-CMS and MPI-ESM-MR show higher skill than the other 7 models in simulating spatial pattern and its decadal change of climate zones over China. The simulation results for FGOALS-g2 and INM-CM4 both show relatively lower skill than the other 7 models. Meanwhile, the performance of multi-model ensemble in simulating climate zones over China is obviously better than the simulated result of any single model. So, it is a good way to simulate climate zones by multi-model ensemble to reduce some uncertainty of climate models. However, it is crucial to select appropriate ensemble members. Compared with 1960–2005, the climatic zones in China have an obvious trend of northward shift in 2021–2100. The range of southern sub-tropical belt expands to the most areas in the south of Yangtze River under RCP4.5 emission scenarios, and further extends to the north areas of Yangtze River with a maximum of 2–6° of latitude under RCP8.5 emission scenarios. Middle sub-tropical belt shifts gradually to the areas between Yellow River and north areas of the middle and lower reaches of the Yangtze River. Northern sub-tropical belt shifts northward to southeastern North China. Warm extra-tropical belt extends to the most of Northeast China, most of central Inner Mongolia, and northern Xinjiang under RCP8.5 emission scenarios.

A Longitudinal Study Investigating Synchronization in a Singing Quintet

Research suggests that synchronization between musicians during ensemble performances can be affected by the rhythmic or tonal complexity of the piece being performed and by group roles such as leader-follower relationships. Since previous studies have mostly been conducted within single performance sessions, developmental aspects of interpersonal synchronization in ensembles remain underinvestigated. This longitudinal study followed a newly formed singing ensemble from initial rehearsals to the performance stage in order to investigate the evolution of synchronization between advanced singing students during a university term of study in relation to the musical content of the piece and leader-follower relationships. An advanced postgraduate singing quintet was recorded using head-worn microphones and laryngograph electrodes to allow fundamental frequency evaluation of the individual voices. The quintet, formed to complete a 1-year Master's programme in ensemble singing, rehearsed two pieces composed for the study, during five rehearsals over 3 months. Singers practised the same pieces in a randomized order across rehearsals and performed three repetitions of the same pieces before and after each rehearsal, resulting in six recordings per piece/rehearsal. Audio and laryngograph data of the repeated performances were collected, and synchronization was measured by extracting note times from the fundamental frequency values. The asynchronies of the two pieces before and after rehearsals were calculated and compared both within rehearsals (pre and post) and between rehearsals (rehearsals 1-5). Results demonstrate an increase in the precision of synchronization over the course of study, depending on the piece being rehearsed, and a more variable synchronization for the more rhythmically complex piece. Results also show changes in the distribution of the tendency to precede all co-performers across rehearsals, which became equally distributed among the musicians during the last rehearsal. The results reported here could have important implications for the tailoring of rehearsal strategies that could improve interpersonal synchronization between musicians during ensemble performances.

Relative model score: a scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling

This paper defines a new scoring rule, namely relative model score (RMS), for evaluating ensemble simulations of environmental models. RMS implicitly incorporates the measures of ensemble mean accuracy, prediction interval precision, and prediction interval reliability for evaluating the overall model predictive performance. RMS is numerically evaluated from the probability density functions of ensemble simulations given by individual models or several models via model averaging. We demonstrate the advantages of using RMS through an example of soil respiration modeling. The example considers two alternative models with different fidelity, and for each model Bayesian inverse modeling is conducted using two different likelihood functions. This gives four single-model ensembles of model simulations. For each likelihood function, Bayesian model averaging is applied to the ensemble simulations of the two models, resulting in two multi-model prediction ensembles. Predictive performance for these ensembles is evaluated using various scoring rules. Results show that RMS outperforms the commonly used scoring rules of log-score, pseudo Bayes factor based on Bayesian model evidence (BME), and continuous ranked probability score (CRPS). RMS avoids the problem of rounding error specific to log-score. Being applicable to any likelihood functions, RMS has broader applicability than BME that is only applicable to the same likelihood function of multiple models. By directly considering the relative score of candidate models at each cross-validation datum, RMS results in more plausible model ranking than CRPS. Therefore, RMS is considered as a robust scoring rule for evaluating predictive performance of single-model and multi-model prediction ensembles.

Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction

Credit risk and corporate bankruptcy prediction has widely been studied as a binary classification problem using both advanced statistical and machine learning models. Ensembles of classifiers have demonstrated their effectiveness for various applications in finance using data sets that are often characterized by imperfections such as irrelevant features, skewed classes, data set shift, and missing and noisy data. However, there are other corruptions in the data that might hinder the prediction performance mainly on the default or bankrupt (positive) cases, where the misclassification costs are typically much higher than those associated to the non-default or non-bankrupt (negative) class. Here we characterize the complexity of 14 real-life financial databases based on the different types of positive samples. The objective is to gain some insight into the potential links between the performance of classifier ensembles (BAGGING, AdaBoost, random subspace, DECORATE, rotation forest, random forest, and stochastic gradient boosting) and the positive sample types. Experimental results reveal that the performance of the ensembles indeed depends on the prevalent type of positive samples.

Collaborative Musical Creativity: How Ensembles Coordinate Spontaneity.

Music performance is inherently social. Most music is performed in groups, and even soloists are subject to influence from a (real or imagined) audience. It is also inherently creative. Performers are called upon to interpret notated music, improvise new musical material, adapt to unexpected playing conditions, and accommodate technical errors. The focus of this paper is how creativity is distributed across members of a music ensemble as they perform these tasks. Some aspects of ensemble performance have been investigated extensively in recent years as part of the broader literature on joint action (e.g., the processes underlying sensorimotor synchronization). Much of this research has been done under highly controlled conditions, using tasks that generate reliable results, but capture only a small part of ensemble performance as it occurs naturalistically. Still missing from this literature is an explanation of how ensemble musicians perform in conditions that require creative interpretation, improvisation, and/or adaptation: how do they coordinate the production of something new? Current theories of creativity endorse the idea that dynamic interaction between individuals, their actions, and their social and material environments underlies creative performance. This framework is much in line with the embodied music cognition paradigm and the dynamical systems perspective on ensemble coordination. This review begins by situating the concept of collaborative musical creativity in the context of embodiment. Progress that has been made toward identifying the mechanisms that underlie collaborative creativity in music performance is then assessed. The focus is on the possible role of musical imagination in facilitating performer flexibility, and on the forms of communication that are likely to support the coordination of creative musical output. Next, emergence and group flow–constructs that seem to characterize ensemble performance at its peak–are considered, and some of the conditions that may encourage periods of emergence or flow are identified. Finally, it is argued that further research is needed to (1) demystify the constructs of emergence and group flow, clarifying their effects on performer experience and listener response, (2) determine how constrained musical imagination is by perceptual experience and understand people's capacity to depart from familiar frameworks and imagine new sounds and sound structures, and (3) assess the technological developments that are supposed to facilitate or enhance musical creativity, and determine what effect they have on the processes underlying creative collaboration.

Synchronization in Singing Duo Performances: The Roles of Visual Contact and Leadership Instruction.

Interpersonal synchronization between musicians during ensemble performances is characterized by continuous micro-timing adjustments due to intentional and unintentional factors supporting expressive interpretations, or caused by noise during the cognitive-motor process. Whether visual contact between musicians and the instruction to act as leader or follower affect synchronization in ensembles remains mostly unclear. This study investigates the role of visual cues and leader-follower relationships in singing performances. Twelve vocal duos took part in the study, singing a two-part piece, which was composed for the study and was mostly homophonic in structure. Four conditions were applied in a randomized order: with and without visual contact, and with a designated leader or follower. The piece was repeated four times in each condition, and the condition presented three times, for a total of 12 performances of the piece in each condition. Data were acquired using electrolaryngograph electrodes and head mounted microphones to track the fundamental frequency estimates of the individual singers. Results show that the presence and absence of visual contact had a significant effect on the precision and consistency of synchronization during singing duo performances. Precision and consistency were better in the presence of visual contact between singers than without, and these effects were associated with the beginning of phonation of the first note of the piece. The presence/absence of visual contact also had an effect on the tendency to lead or lag a co-performer associated with the onset of the first note; the extent of leading was greater when visual contact was absent. The instruction to act as leader or follower did not affect precision or consistency of synchronization, nor did it relate to the observed tendency to precede or lag a co-performer. The results contribute to the tailoring of rehearsal strategies, as singers and directors can be better informed of the factors influencing synchronization and focus on specific areas of difficulty in certain performance conditions, such as first note onsets when performers are not able to see each other.

Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada

Climate ensembles utilize outputs from multiple climate models to estimate future climate patterns. These multi-model ensembles generally outperform individual climate models. In this paper, the performance of seven global climate model and regional climate model combinations were evaluated for Ontario, Canada. Two multi-model ensembles were developed and tested, one based on the mean of the seven combinations and the other based on the median of the same seven models. The performance of the multi-model ensembles were evaluated on 12 meteorological stations, as well as for the entire domain of Ontario, using three temperature variables (average surface temperature, maximum surface temperature, and minimum surface temperature). Climate data for developing and validating the multi-model ensembles were collected from three major sources: the North American Coordinated Regional Downscaling Experiment, the Digital Archive of Canadian Climatological Data, and the Climactic Research Unit’s TS v4.00 dataset. The results showed that the climate ensemble based on the mean generally outperformed the one based on the median, as well as each of the individual models. Future predictions under the Representative Concentration Pathway 4.5 (RCP4.5) scenario were generated using the multi-model ensemble based on the mean. This study provides credible and useful information for climate change mitigation and adaption in Ontario.

A Model Ensemble for Projecting Multidecadal Coastal Cliff Retreat During the 21st Century

AbstractSea cliff retreat rates are expected to accelerate with rising sea levels during the 21st century. Here we develop an approach for a multimodel ensemble that efficiently projects time‐averaged sea cliff retreat over multidecadal time scales and large (>50 km) spatial scales. The ensemble consists of five simple 1‐D models adapted from the literature that relate sea cliff retreat to wave impacts, sea level rise (SLR), historical cliff behavior, and cross‐shore profile geometry. Ensemble predictions are based on Monte Carlo simulations of each individual model, which account for the uncertainty of model parameters. The consensus of the individual models also weights uncertainty, such that uncertainty is greater when predictions from different models do not agree. A calibrated, but unvalidated, ensemble was applied to the 475‐km‐long coastline of Southern California (USA), with four SLR scenarios of 0.5, 0.93, 1.5, and 2 m by 2100. Results suggest that future retreat rates could increase relative to mean historical rates by more than twofold for the higher SLR scenarios, causing an average total land loss of 19–41 m by 2100. However, model uncertainty ranges from ±5 to 15 m, reflecting the inherent difficulties of projecting cliff retreat over multiple decades. To enhance ensemble performance, future work could include weighting each model by its skill in matching observations in different morphological settings.

Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?

In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)-Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13-16 % compared to G and by 2-3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.