Dynamical Modeling of the Grand Piano Action

Frontiers in signal processing, 2024

Numerical emulations of the piano have been a subject of study since the early days of sound synthesis. High-accuracy sound synthesis of acoustic instruments employs physical modeling techniques which aim to describe the system's internal mechanism using mathematical formulations. Such physical approaches are system-specific and present significant challenges for tuning the system's parameters. In addition, acoustic instruments such as the piano present nonlinear mechanisms that present significant computational challenges for solving associated partial differential equations required to generate synthetic sound. In a nonlinear context, the stability and efficiency of the numerical schemes when performing numerical simulations are not trivial, and models generally adopt simplifying assumptions and linearizations. Artificial neural networks can learn a complex system's behaviors from data, and their application can be beneficial for modeling acoustic instruments. Artificial neural networks typically offer less flexibility regarding the variation of internal parameters for interactive applications, such as real-time sound synthesis. However, their integration with traditional signal processing frameworks can overcome this limitation. This article presents a method for piano sound synthesis informed by the physics of the instrument, combining deep learning with traditional digital signal processing techniques. The proposed model learns to synthesize the quasi-harmonic content of individual piano notes using physicsbased formulas whose parameters are automatically estimated from real audio recordings. The model thus emulates the inharmonicity of the piano and the amplitude envelopes of the partials. It is capable of generalizing with good accuracy across different keys and velocities. Challenges persist in the highfrequency part of the spectrum, where the generation of partials is less accurate, especially at high-velocity values. The architecture of the proposed model permits low-latency implementation and has low computational complexity, paving the way for a novel approach to sound synthesis in interactive digital pianos that emulates specific acoustic instruments.

Proc. of the Workshop …, 2001

Computer Animation and Virtual Worlds, 2012

Playing the piano requires one to precisely position one's hand in order to strike particular combinations of keys at specific moments in time. This paper presents the first system for automatically generating three-dimensional animations of piano performance, given an input midi music file. A graph theory-based motion planning method is used to decide which set of fingers should strike the piano keys for each chord. As the progression of the music is anticipated, the positions of unused fingers are calculated to make possible efficient fingering of future notes. Initial key poses of the hands, including those for complex piano techniques such as crossovers and arpeggio, are determined on the basis of the finger positions and piano theory. An optimization method is used to refine these poses, producing a natural and minimal energy pose sequence. Motion transitions between poses are generated using a combination of sampled piano playing motion and music features, allowing the system to support different playing styles. Our approach is validated through direct comparison with actual piano playing and simulation of a complete music piece requiring various playing skills. Extensions of our system are discussed.

SIGGRAPH '09: Posters on - SIGGRAPH '09, 2009

It is desirable in the field of animation and music education to develop a technique for piano performance animation using Computer Graphics. However, previous techniques for computer animation of piano performance have been mechanical and tended to lack the reality of fingering motions. This study is to develop techniques to reproduce the piano playing with fine motion by using detailed and natural-looking-computer graphics. In this paper, three studies have been described; (i) measurement of piano fingering using motion capture technology, (ii) generation of a CG animation of fingering using offline/real-time rendering, and (iii) automatic generation of fingering using optimized algorithms. Finally examples in which the fingering data created in (i) is used in TV animation "Nodame Cantabile", a Japanese comic book, has been introduced.

1999

In this paper we discuss the real-time simulation of a physical model of a bowed string instrument by means of alternative gestural controllers. We focus on the model's behaviour when submitted to di erent b o w strokes performed on a graphical tablet using di erent t ypes transducers. The tablet was chosen because it allows a performer to reproduce most of the basic physical gestures of bow strokes in a natural way.

2005

This study investigated the temporal behavior of grand piano actions from different manufacturers under different touch conditions and dynamic levels. An experimental setup consisting of accelerometers and a calibrated microphone was used to capture key and hammer movements, as well as the sound signal. Five selected keys were played by pianists with two types of touch (“pressed touch” versus “struck touch”) over the entire dynamic range.

The Journal of the …, 2002

For sound synthesis purposes, the vibration of a piano string may be simply modeled using bidirectional delay lines or digital waveguides which transport traveling wave-like signals in both directions. Such a digital wavetype formulation, in addition to yielding a particularly computationally efficient simulation routine, also possesses other important advantages. In particular, it is possible to couple the delay lines to a nonlinear exciting mechanism (the hammer) without compromising stability; in fact, if the hammer and string are lossless, their digital counterparts will be exactly lossless as well. The key to this good property (which can be carried over to other nonlinear elements in musical systems) is that all operations are framed in terms of the passive scattering of discrete signals in the network, the sum-of-squares of which serves as a discrete-time Lyapunov function for the system as a whole. Simulations are presented.

Computer Music Journal, 2011

2020

Today, one of the most important issues in designing of structures is their reliability and functional design. In order to obtain reliability, different parameters of the earthquake history are considered as probabilistic and that their effects on the reliability of the structures. In fact, it is necessary to consider all possible scenarios in the earthquake event in the probability of failure of the structure, which is recorded using natural ground motions. In response to this engineering requirements, the use of simulated artificial earthquake records is one alternative. Therefore the most important point in using artificial records is to use a model that can more effectively capture the effective parameters in earthquake production. In this case, by obtaining uncertainties regarding the efficient parameters in that model, it is possible to produce an accidental earthquake production. In this study, the use of piano keys was applied as an artificial record. To achieve this goal, 6...

Computer music journal, 1996