Operating Sound Parameters Using Markov Model and Bayesian Filters in Automated Music Performance

نویسندگان

  • Fumito Hashimoto
  • Motoki Miura
چکیده

In recent years, there has been an increase in the number of artists who make use of automated music performances in their music and live concerts. Automated music performance is a form of music production using programmed musical notes. Some artists who introduce automated music performance operate parameters of the sound in their performance for production of their music. In this paper, we focus on the music production aspects and describe a method that realizes operation of the sound parameters via computer. Further, in this study, the probability distribution of the action (i.e., variation of parameters) is obtained within the music, using Bayesian filters. The probability distribution of each piece of music is transformed by passing through a Markov model. After the probability distribution is obtained, sound parameters can be automatically controlled. We have developed a system to reproduce the musical expressions of humans and confirmed the possibilities of our method.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Learning Bayesian Network Structure using Markov Blanket in K2 Algorithm

‎A Bayesian network is a graphical model that represents a set of random variables and their causal relationship via a Directed Acyclic Graph (DAG)‎. ‎There are basically two methods used for learning Bayesian network‎: ‎parameter-learning and structure-learning‎. ‎One of the most effective structure-learning methods is K2 algorithm‎. ‎Because the performance of the K2 algorithm depends on node...

متن کامل

Application of Markov-Chain Analysis and Stirred Tanks in Series Model in Mathematical Modeling of Impinging Streams Dryers

In spite of the fact that the principles of impinging stream reactors have been developed for more than half a century, the performance analysis of such devices, from the viewpoint of the mathematical modeling, has not been investigated extensively. In this study two mathematical models were proposed to describe particulate matter drying in tangential impinging stream dryers. The models were de...

متن کامل

Markov Logarithmic Series Distribution and Estimation of its Parameters by Method of E-Bayesian

In the analysis of Bernoulli's variables, an investigation of the their dependence is of the prime importance. In this paper, the distribution of the Markov logarithmic series is introduced by the execution of the first-order dependence among Bernoulli variables. In order to estimate the parameters of this distribution, maximum likelihood, moment, Bayesian and also a new method which called the...

متن کامل

A Disease Outbreak Prediction Model Using Bayesian Inference: A Case of Influenza

Introduction: One major problem in analyzing epidemic data is the lack of data and high dependency among the available data, which is due to the fact that the epidemic process is not directly observable. Methods: One method for epidemic data analysis to estimate the desired epidemic parameters, such as disease transmission rate and recovery rate, is data ...

متن کامل

Automated Tumor Segmentation Based on Hidden Markov Classifier using Singular Value Decomposition Feature Extraction in Brain MR images

ntroduction: Diagnosing brain tumor is not always easy for doctors, and existence of an assistant that                                                      facilitates the interpretation process is an asset in the clinic. Computer vision techniques are devised to aid the clinic in detecting tumors based on a database of tumor c...

متن کامل

ذخیره 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 نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014