Acoustical Correlates of Timbre and Expressiveness in Clarinet Performance

2010 ◽  
Vol 28 (2) ◽  
pp. 135-154 ◽  
Author(s):  
Mathieu Barthet ◽  
Philippe Depalle ◽  
Richard Kronland-Martinet ◽  
Søølvi Ystad
Keyword(s):  
Root Mean Square ◽  
Analysis Of Variance ◽  
Mean Square ◽  
Spectral Centroid ◽  
Independent Variables ◽  
Musical Excerpts ◽  
Clarinet Performance ◽  
Recorded Performances ◽  
Attack Time

This study deals with the acoustical factors liable to account for expressiveness in clarinet performances. Mechanical and expressive performances of excerpts from Bach's Suite No. II and Mozart's Quintet for Clarinet and Strings were recorded. Timbre, timing, dynamics, and pitch descriptors were extracted from the recorded performances. The data were processed using a two-way analysis of variance, where the musician's expressive intentions and the note factors were defined as the independent variables. In both musical excerpts, a strong effect of the expressive intention was observed on the timbre (attack time, spectral centroid, odd/even ratio), timing (intertone onset intervals) and dynamics (root mean square envelope) descriptors. The changes in the timbre descriptors were found to depend on the position of the notes in the musical phrases. These results suggest that timbre, as well as timing and dynamics variations, may mediate expressiveness in the musical messages transmitted from performers to listeners.

Analysis-By-Synthesis of Timbre, Timing, and Dynamics in Expressive Clarinet Performance

2011 ◽  
Vol 28 (3) ◽  
pp. 265-278 ◽  
Author(s):  
Mathieu Barthet ◽  
Philippe Depalle ◽  
Richard Kronland-Martinet ◽  
Søølvi Ystad
Keyword(s):  
Paired Comparison ◽  
Mean Square ◽  
Acoustical Parameters ◽  
Comparison Task ◽  
Spectral Centroid ◽  
Musical Preference ◽  
Clarinet Performance ◽  
Analysis By Synthesis ◽  
Synthesis Approach ◽  
Acoustical Energy

In a Previous Study, Mechanical and Expressive clarinet performances of Bach's Suite No. II and Mozart's Quintet for Clarinet and Strings were analyzed to determine whether some acoustical correlates of timbre (e.g., spectral centroid), timing (intertone onset interval), and dynamics (root mean square envelope) showed significant differences depending on the expressive intention of the performer. In the present companion study, we investigate the effects of these acoustical parameters on listeners' preferences. An analysis-by-synthesis approach was used to transform previously recorded clarinet performances by reducing the expressive deviations from the spectral centroid, the intertone onset interval and the acoustical energy. Twenty skilled musicians were asked to select which version they preferred in a paired comparison task. The results of statistical analyses showed that the removal of the spectral centroid variations resulted in the greatest loss of musical preference.

scholarly journals Influence of mentalis muscle relaxation on oronasal breathing

Revista CEFAC ◽  
2021 ◽  
Vol 23 (2) ◽  
Author(s):  
Mara Letícia Gobbis ◽  
Bruno Luis Amoroso Borges ◽  
Karina Aparecida Tramonti ◽  
Cynthia Lopes da Silva ◽  
Mirian Hideko Nagae
Keyword(s):  
Standard Deviation ◽  
Root Mean Square ◽  
Analysis Of Variance ◽  
Muscle Relaxation ◽  
Massage Therapy ◽  
Control Group ◽  
Mean Square ◽  
Significance Level ◽  
Significant Difference ◽  
Experimental Group

ABSTRACT Purpose: to investigate the existence of changes in the electromyographic patterns of the mentalis and inferior orbicularis oris muscles in oronasal breathers, submitted to massage therapy on the mentalis muscle. Methods: a controlled blind placebo experiment, with a sample of 19 oronasal breathers (1 man and 18 women), mean age (standard deviation) 22.3 (2.63) years, randomly divided into control and experimental groups, respectively with 7 and 12 volunteers. The experimental group alone underwent myotherapy with massages for 3 months, while electromyographic data were collected from both groups at the beginning and end of the treatment, both at rest and when swallowing water. The analysis of variance was conducted to test the existence of differences between the means; the 5% significance level was used. Results: the analysis of variance revealed signs of interaction between the group and phase effects when analyzing the root mean square values of both the inferior orbicularis oris and the mentalis muscles. As expected, no signs of significant differences were found between the means of the phases in the control group. On the other hand, signs of significant difference were found in the experimental group, with reduced root mean square values in both muscles. The inferior orbicularis oris muscle, which in the pre-phase had a mean (standard deviation) of 202.10 (161.47) µV, had, in the post-phase, values of 131.49 (159.18) µV. The mentalis muscle, in its turn, had in the pre- and post-phase, respectively, a mean (standard deviation) of 199.31 (279.77) µV and 114.58 (253.56) µV. Conclusion: given that no effect was detected in the control group, the decrease in the root mean square values of the mentalis and inferior orbicularis oris muscles in oronasal breathers was attributed to the massage therapy on the mentalis muscle.

scholarly journals A novel prediction algorithm for multivariate data sets

2021 ◽  
Vol 4 (2) ◽  
pp. 225-240
Author(s):  
Pinki Sagar ◽  
◽  
Prinima Gupta ◽  
Rohit Tanwar ◽  
◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Multivariate Data ◽  
Prediction Algorithm ◽  
Series Data ◽  
Data Sets ◽  
Mean Square ◽  
Data Set ◽  
Independent Variables

Regression analysis is a statistical technique that is most commonly used for forecasting. Data sets are becoming very large due to continuous transactions in today's high-paced world. The data is difficult to manage and interpret. All the independent variables can’t be considered for the prediction because it costs high for maintenance of the data set. A novel algorithm for prediction has been implemented in this paper. Its emphasis is on extraction of efficient independent variables from various variables of the data set. The selection of variables is based on Mean Square Errors (MSE) as well as on the coefficient of determination r2p, after that the final prediction equation for the algorithm is framed on the basis of deviation of actual mean. This is a statistical based prediction algorithm which is used to evaluate the prediction based on four parameters: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and residuals. This algorithm has been implemented for a multivariate data set with low maintenance costs, preprocessing costs, lower root mean square error and residuals. For one dimensional, two-dimensional, frequent stream data, time series data and continuous data, the proposed prediction algorithm can also be used. The impact of this algorithm is to enhance the accuracy rate of forecasting and minimized average error rate.

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

scholarly journals Estimation of Apple Flowering Frost Loss for Fruit Yield Based on Gridded Meteorological and Remote Sensing Data in Luochuan, Shaanxi Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Price Regulation ◽  
Flowering Period ◽  
Mean Square ◽  
Prevention Measures ◽  
Agricultural Insurance

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

Intersession reliability of GPS-based and accelerometer-based physical variables in small-sided games with and without the offside rule

2021 ◽  
pp. 175433712098764
Author(s):  
Igor Junio de Oliveira Custódio ◽  
Gibson Moreira Praça ◽  
Leandro Vinhas de Paula ◽  
Sarah da Glória Teles Bredt ◽  
Fabio Yuzo Nakamura ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Positioning System ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Mean Square ◽  
Physical Demands ◽  
Intraclass Correlation Coefficients ◽  
Total Distance ◽  
Global Positioning ◽  
High Level

This study aimed to analyze the intersession reliability of global positioning system (GPS-based) distances and accelerometer-based (acceleration) variables in small-sided soccer games (SSG) with and without the offside rule, as well as compare variables between the tasks. Twenty-four high-level U-17 soccer athletes played 3 versus 3 (plus goalkeepers) SSG in two formats (with and without the offside rule). SSG were performed on eight consecutive weeks (4 weeks for each group), twice a week. The physical demands were recorded using a GPS with an embedded triaxial accelerometer. GPS-based variables (total distance, average speed, and distances covered at different speeds) and accelerometer-based variables (Player Load™, root mean square of the acceleration recorded in each movement axis, and the root mean square of resultant acceleration) were calculated. Results showed that the inclusion of the offside rule reduced the total distance covered (large effect) and the distances covered at moderate speed zones (7–12.9 km/h – moderate effect; 13–17.9 km/h – large effect). In both SSG formats, GPS-based variables presented good to excellent reliability (intraclass correlation coefficients – ICC > 0.62) and accelerometer-based variables presented excellent reliability (ICC values > 0.89). Based on the results of this study, the offside rule decreases the physical demand of 3 versus 3 SSG and the physical demands required in these SSG present high intersession reliability.

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