Audio fingerprinting allows us to label an unidentified music fragment within a previously generated database. The use of spectral landmarks aims to obtain a robustness that lets a certain level of noise be present in the audio query. This group of audio identification algorithms holds several configuration parameters whose values are usually chosen based upon the researcher’s knowledge, previous published experimentation or just trial and error methods. In this paper we describe the whole optimisation process of a Landmark-based Music Recognition System using genetic algorithms. We define the actual structure of the algorithm as a chromosome by transforming its high relevant parameters into various genes and building up an appropriate fitn...
This paper presents a simple approach for implementing Interactive Evolutionary Computation (IEC) - ...
This paper describes the use of genetic algorithims for the automatic generation of music, by means ...
This is an electronic version of the paper presented at the WSEAS International Conference on Artifi...
This study explores the use of genetic algorithms (GA) in optimising feature selection for musical i...
This paper describes a research work in which we study the possibility of applying genetic algorithm...
This study uses Genetic Programming (GP) in developing a classi er to distinguish between ve musica...
Thesis (B.S.)--University of Rochester. Dept. of Computer Science, 2006.Polyphonic music transcript...
Choosing good features is an essential part of machine learning. Recent techniques aim to automate t...
Research object: the adaptation and application of the genetic algorithm for electrodynamic transduc...
Abstract:- In this paper, a very efficient novel methodology for the automatic recognition of musica...
The focus of this bachelor thesis is to generate appealing music segments algorithmically. Since its...
In this paper we present a new acoustic fingerprinting system, based on pitch class histograms. The ...
A genetic algorithm selected combinations of attributes for a machine learning system. The algorithm...
Music classification continues to be an important component of music information retrieval research....
This paper presents a procedure which composes music pieces through handling four layers in music, n...
This paper presents a simple approach for implementing Interactive Evolutionary Computation (IEC) - ...
This paper describes the use of genetic algorithims for the automatic generation of music, by means ...
This is an electronic version of the paper presented at the WSEAS International Conference on Artifi...
This study explores the use of genetic algorithms (GA) in optimising feature selection for musical i...
This paper describes a research work in which we study the possibility of applying genetic algorithm...
This study uses Genetic Programming (GP) in developing a classi er to distinguish between ve musica...
Thesis (B.S.)--University of Rochester. Dept. of Computer Science, 2006.Polyphonic music transcript...
Choosing good features is an essential part of machine learning. Recent techniques aim to automate t...
Research object: the adaptation and application of the genetic algorithm for electrodynamic transduc...
Abstract:- In this paper, a very efficient novel methodology for the automatic recognition of musica...
The focus of this bachelor thesis is to generate appealing music segments algorithmically. Since its...
In this paper we present a new acoustic fingerprinting system, based on pitch class histograms. The ...
A genetic algorithm selected combinations of attributes for a machine learning system. The algorithm...
Music classification continues to be an important component of music information retrieval research....
This paper presents a procedure which composes music pieces through handling four layers in music, n...
This paper presents a simple approach for implementing Interactive Evolutionary Computation (IEC) - ...
This paper describes the use of genetic algorithims for the automatic generation of music, by means ...
This is an electronic version of the paper presented at the WSEAS International Conference on Artifi...