Calibrationof Physicalmodels Using Artificial Neural Networks with Application to Plucked String Instruments
نویسندگان
چکیده
This study introduces a method for estimating the model parameters of plucked string instruments using artiicial neural networks (ANN's). The system consists of a preprocessor and an ANN model. The prepro-cessor computes the time-varying harmonics of recorded sounds and this data is fed into the ANN model to implement the nonlinear mapping to the parameter space. The main advantage of this method is that it performs the mapping according to a perceptual measure derived from listening tests.
منابع مشابه
A class of physical modeling recurrent networks for analysis/synthesis of plucked string instruments
A new approach is proposed that closely synthesizes tones of plucked string instruments by using a class of physical modeling recurrent networks. The strategies employed consist of a fast training algorithm and a multistage training procedure that are able to obtain the synthesis parameters for a specific instrument automatically. The training vector can be recorded tones of most target plucked...
متن کاملModel-based synthesis of plucked string instruments by using a class of scattering recurrent networks
A physical modeling method for electronic music synthesis of plucked-string tones by using recurrent networks is proposed. A scattering recurrent network (SRN) which is used to analyze string dynamics is built based on the physics of acoustic strings. The measured vibration of a plucked string is employed as the training data for the supervised learning of the SRN. After the network is well tra...
متن کاملPhysical Modeling of Plucked String Instruments with Application to Real-Time Sound Synthesis*
An efficient approach for real-time synthesis of plucked string instruments using physical modeling and DSP techniques is presented. Results of model-based resynthesis are illustrated to demonstrate that high-quality synthetic sounds of several string instruments can be generated using the proposed modeling principles. Real-time implementation using a signal processor is described, and several ...
متن کاملEstimation of Daily Evaporation Using of Artificial Neural Networks (Case Study; Borujerd Meteorological Station)
Evaporation is one of the most important components of hydrologic cycle.Accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. In order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. Using direct methods require installing meteorological stations andinstruments ...
متن کاملFlood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1997