Musical Genre Classification and Musical Similarity Determination from Audio
This event took place on Thursday 10 May 2007 at 11:30
Professor Stephen Cox School of Computing Sciences, University of East Anglia, Norwich, UK
Recently, there has been a revolution in the way that music has been delivered to users. The universal availability of broadband to the home and the development of cheap, high-capacity MP3 players has led to an exponential growth in music distribution over the internet, and to the emergence of large personal collections of songs held on users computers and players. This in turn has led to a need for effective techniques for organising, browsing and visualising music collections and generating playlists. Although metadata giving details of e.g. the track title, the album, the artists etc. is available for much of the music available on the web, it is not universal, and this data is usually not detailed enough to implement the above techniques to a high standard. We have been investigating techniques for automatically classifying the genre of a song and measuring the similarity of two songs using only the audio signal. I will describe our approach to these two related tasks, and present results that suggest it is possible to perform them with reasonable accuracy. I will also demonstrate our musical similarity software that suggests songs similar to an input song from a 5000 song collection.
This event took place on Thursday 10 May 2007 at 11:30
Recently, there has been a revolution in the way that music has been delivered to users. The universal availability of broadband to the home and the development of cheap, high-capacity MP3 players has led to an exponential growth in music distribution over the internet, and to the emergence of large personal collections of songs held on users computers and players. This in turn has led to a need for effective techniques for organising, browsing and visualising music collections and generating playlists. Although metadata giving details of e.g. the track title, the album, the artists etc. is available for much of the music available on the web, it is not universal, and this data is usually not detailed enough to implement the above techniques to a high standard. We have been investigating techniques for automatically classifying the genre of a song and measuring the similarity of two songs using only the audio signal. I will describe our approach to these two related tasks, and present results that suggest it is possible to perform them with reasonable accuracy. I will also demonstrate our musical similarity software that suggests songs similar to an input song from a 5000 song collection.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Semantic Web and Knowledge Services is...
Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.
List all Semantic Web and Knowledge Services Projects
Check out these Hot Semantic Web and Knowledge Services Technologies:
List all Semantic Web and Knowledge Services Technologies
