This paper briefly reports on recent advances in the development of search engines for music and audio within the MiDiLiB project: whilenotify! is a tool for searching in symbolic music data like MIDI,audentify! allows to search in PCM audio.

The phenomenal growth in popularity of the World Wide Web (WWW, or the Web) has made WWW traffic the largest contributor to packet and byte traffic on the NSFNET backbone. This growth has triggered recent research aimed at reducing the volume of network traffic produced by Web clients and servers, by using caching, and reducing the latency for WWW users, by using improved protocols for Web interaction. Fundamental to the goal of improving WWW performance is an understanding of WWW workloads. This paper presents a workload characterization study for Internet Web servers. Six different data sets are used in this study: three from academic environments, two from scientific research organizations, and one from a commercial Internet provider. These data sets represent three different orders of magnitude in server activity, and two different orders of magnitude in time duration, ranging from one week of activity to one year of activity. Throughout the study, emphasis is placed on finding wor...

audio classification and retrieval using a fuzzy logic system: towards multimedia search engines

requires content-based retrieval strategies which only utilize the raw audio material. In this contribution, we discuss content-based retrieval strategies that follow the query-by-example paradigm: given an audio query, the task is to retrieve all documents that are somehow similar or related to the query

In this paper we explore a technique for content-based music retrieval using a continuous pitch contour derived from a recording of the audio query instead of a quantization of the query into discrete notes. Our system determines the pitch for each unit of time in the query and then uses a time

of content-based transformations. Then we take a quick look at a general spectral based analysis/synthesis approach to process audio signals and how to extract features that can be used in the content-based transformation context. Using this analysis/synthesis approach we give some examples on how content-based

Abstract:- A This paper describes a method of content indexing for Multimedia Databases using binary signatures for MIDI format archives. The analysis scheme focuses on the primary audio objects of the Multimedia environment, applies a reduction mechanism and extracts characteristic patterns

Getting computers to understand and process audio recordings in terms of their musical content is a difficult challenge. We describe a method in which general, polyphonic audio recordings of music can be aligned to symbolic score information in standard MIDI files. Because of the difficulties

Rapid increase in the amount of audio data and especially music collections demand an efficient method to automatically retrieve audio objects based on its content. In this paper, based on the Gabor wavelet features, we will propose a method for content-based retrieval of perceptually similar music

Getting computers to understand and process audio recordings in terms of their musical content is a difficult challenge. We describe a method in which general, polyphonic audio recordings of music can be aligned to symbolic score information in standard MIDI files. Because of the difficulties