Audio Indexing

The enormous amount of unstructured audio data available nowadays and the spread of its use as a data source in many applications are introducing new challenges to researchers in information and signal processing. The continuously growing size of digital audio information increases the difficulty of its access and management, thus hampering its practical usefulness. As a consequence, the need for content-based audio data parsing, indexing and retrieval techniques to make the digital information more readily available to the user is becoming ever more critical. The lack of proper indexing and retrieval systems is making de facto useless significant portions of existing audio information (and obviously audiovisual information in general). In fact, if generating digital content is easy and cheap, managing and structuring it to produce effective services is clearly not. This applies to the whole range of content providers and broadcasters which can amount to terabytes of audio and audiovisual data. It also applies to the audio content gathered in private collection of digital movies or music files stored in the hard disks of conventional personal computers. In summary, the goal of an audio indexing system will then be to automatically extract high-level information from the digital raw audio in order to provide new means to navigate and search in large audio databases. Since it is not possible to cover all applications of audio indexing, the basic concepts described in this chapter will be mainly illustrated on the specific problem of musical instrument recognition.