Search
Now showing items 1-10 of 26
Toward the Scientific Evaluation of Music Information Retrieval Systems
(Johns Hopkins University, 2003-10-26)
This paper outlines the findings-to-date of a project to assist in the efforts being made to establish a TREC-like evaluation paradigm within the Music Information Retrieval (MIR) research community. The findings and ...
Features for audio and music classification
(Johns Hopkins University, 2003-10-26)
Four audio feature sets are evaluated in their ability to classify five general audio classes and seven popular music genres. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and ...
Blind Clustering of Popular Music Recordings Based on Singer Voice Characteristics
(Johns Hopkins University, 2003-10-26)
This paper presents an effective technique for automatically clustering undocumented music recordings based on their associated singer. This serves as an indispensable step towards indexing and content-based information ...
The C-BRAHMS project
(Johns Hopkins University, 2003-10-26)
The C-BRAHMS project develops computational methods for content-based retrieval and analysis of music data. A summary of the recent algorithmic and experimental developments of the project is given. A search engine developed ...
Automatic Segmentation, Learning and Retrieval of Melodies Using A Self-Organizing Neural Network
(Johns Hopkins University, 2003-10-26)
We introduce a neural network, known as SONNET-MAP, capable of automatic segmentation, learning and retrieval of melodies. SONNET-MAP is a synthesis of Nigrin’s SONNET (Self-Organizing Neural NETwork) architecture and an ...
Design Patterns in XML Music Representation
(Johns Hopkins University, 2003-10-26)
Design patterns attempt to formalize the discussion of recurring problems and their solutions. This paper introduces several XML design patterns and demonstrates their usefulness in the development of XML music representations. ...
Quantitative Comparisons into Content-Based Music Recognition with the Self Organising Map
(Johns Hopkins University, 2003-10-26)
With so much modern music being so widely available both in electronic form and in more traditional physical formats, a great opportunity exists for the development of a general-purpose recognition and music classification ...
The dangers of parsimony in query-by-humming applications
(Johns Hopkins University, 2003-10-26)
Query-by-humming systems attempt to address the needs of the non-expert user, for whom the most natural query format -- for the purposes of finding a tune, hook or melody of unknown providence -- is to sing it. While human ...
The MUSART Testbed for Query-By-Humming Evaluation
(Johns Hopkins University, 2003-10-26)
Evaluating music information retrieval systems is acknowledged to be a difficult problem. We have created a database and a software testbed for the systematic evaluation of various query-by-humming (QBH) search systems. ...
Effectiveness of HMM-Based Retrieval on Large Databases
(Johns Hopkins University, 2003-10-26)
We have investigated the performance of a hidden Markov model based QBH retrieval system on a large musical database. The database is synthetic, generated from statistics gleaned from our (smaller) database of musical ...