The Audio Degradation Toolbox and its Application to Robustness Evaluation

We introduce the Audio Degradation Toolbox (ADT) for the controlled degradation of audio signals, and propose its usage as a means of evaluating and comparing the robustness of audio processing algorithms. Music recordings encountered in practical applications are subject to varied, sometimes unpredictable degradation. For example, audio is degraded by low-quality microphones, noisy recording environments, MP3 compression, dynamic compression in broadcasting or vinyl decay. In spite of this, no standard software for the degradation of audio exists, and music processing methods are usually evaluated against clean data. The ADT fills this gap by providing Matlab scripts that emulate a wide range of degradation types. We describe 14 degradation units, and how they can be chained to create more complex, `real-world' degradations. The ADT also provides functionality to adjust existing ground-truth, correcting for temporal distortions introduced by degradation. Using four different music informatics tasks, we show that performance strongly depends on the combination of method and degradation applied. We demonstrate that specific degradations can reduce or even reverse the performance difference between two competing methods. ADT source code, sounds, impulse responses and definitions are freely available for download

Information Retrieval Models

Many applications that handle information on the internet would be completely\ud inadequate without the support of information retrieval technology. How would\ud we find information on the world wide web if there were no web search engines?\ud How would we manage our email without spam filtering? Much of the development\ud of information retrieval technology, such as web search engines and spam\ud filters, requires a combination of experimentation and theory. Experimentation\ud and rigorous empirical testing are needed to keep up with increasing volumes of\ud web pages and emails. Furthermore, experimentation and constant adaptation\ud of technology is needed in practice to counteract the effects of people that deliberately\ud try to manipulate the technology, such as email spammers. However,\ud if experimentation is not guided by theory, engineering becomes trial and error.\ud New problems and challenges for information retrieval come up constantly.\ud They cannot possibly be solved by trial and error alone. So, what is the theory\ud of information retrieval?\ud There is not one convincing answer to this question. There are many theories,\ud here called formal models, and each model is helpful for the development of\ud some information retrieval tools, but not so helpful for the development others.\ud In order to understand information retrieval, it is essential to learn about these\ud retrieval models. In this chapter, some of the most important retrieval models\ud are gathered and explained in a tutorial style

Information retrieval system

Generalized information storage and retrieval system capable of generating and maintaining a file, gathering statistics, sorting output, and generating final reports for output is reviewed. File generation and file maintenance programs written for the system are general purpose routines

Drum Transcription via Classification of Bar-level Rhythmic Patterns

acceptedMatthias Mauch is supported by a Royal Academy of Engineering Research Fellowshi

MIREX: MapReduce Information Retrieval Experiments

We propose to use MapReduce to quickly test new retrieval approaches on a cluster of machines by sequentially scanning all documents. We present a small case study in which we use a cluster of 15 low cost ma- chines to search a web crawl of 0.5 billion pages showing that sequential scanning is a viable approach to running large-scale information retrieval experiments with little effort. The code is available to other researchers at: http://mirex.sourceforge.ne

Children’s information retrieval: beyond examining search strategies and interfaces

The study of children’s information retrieval is still for the greater part untouched territory. Meanwhile, children can become lost in the digital information world, because they are confronted with search interfaces, both designed by and for adults. Most current research on children’s information retrieval focuses on examining children’s search performance on existing search interfaces to determine what kind of interfaces are suitable for children’s search behaviour. However, to discover the true nature of children’s search behaviour, we state that research has to go beyond examining search strategies used with existing search interfaces by examining children’s cognitive processes during information-seeking. A paradigm of children’s information retrieval should provide an overview of all the components beyond search interfaces and search strategies that are part of children’s information retrieval process. Better understanding of the nature of children’s search behaviour can help adults design interfaces and information retrieval systems that both support children’s natural search strategies and help them find their way in the digital information world