What were you expecting? Using Expectancy Features to Predict Expressive Performances of Classical Piano Music
نویسندگان
چکیده
In this paper we present preliminary work examining the relationship between the formation of expectations and the realization of musical performances, paying particular attention to expressive tempo and dynamics. To compute features that reflect what a listener is expecting to hear, we employ a computational model of auditory expectation called the Information Dynamics of Music model (IDyOM). We then explore how well these expectancy features – when combined with score descriptors using the Basis-Function modeling approach – can predict expressive tempo and dynamics in a dataset of Mozart piano sonata performances. Our results suggest that using expectancy features significantly improves the predictions for tempo.
منابع مشابه
Polyhymnia: An Automatic Piano Performance System with Statistical Modeling of Polyphonic Expression and Musical Symbol Interpretation
We developed an automatic piano performance system called Polyhymnia that is able to generate expressive polyphonic piano performances with music scores so that it can be used as a computer-based tool for an expressive performance. The system automatically renders expressive piano music by means of automatic musical symbol interpretation and statistical models of structure-expression relations ...
متن کاملExpressive timing analysis in classical piano performance by mathematical model selection
Given a piece of music, the timing of each beat varies from performer to performer. The study of these small differences is known as expressive timing analysis. Research into expressive timing helps us to understand human perception of music and the production of enjoyable music. Classical piano music is one music style where it is possible to measure expressive timing and hence provides a prom...
متن کاملAn Evaluation of Score Descriptors Combined with Non-linear Models of Expressive Dynamics in Music
Expressive interpretation forms an important but complex aspect of music, in particular in certain forms of classical music. Modeling the relation between musical expression and structural aspects of the score being performed, is an ongoing line of research. Prior work has shown that some simple numerical descriptors of the score (capturing dynamics annotations and pitch) are effective for pred...
متن کاملJazz Ensemble Expressive Performance Modeling
Computational expressive music performance studies the analysis and characterisation of the deviations that a musician introduces when performing a musical piece. It has been studied in a classical context where timing and dynamic deviations are modeled using machine learning techniques. In jazz music, work has been done previously on the study of ornament prediction in guitar performance, as w...
متن کاملPredicting Expressive Dynamics in Piano Performances using Neural Networks
This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data describing more than 6000 musical pieces is used; when training for prediction, two datasets are used...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/1709.03629 شماره
صفحات -
تاریخ انتشار 2017