Tools for Searching, Annotation and Analysis of Speech, Music, Film and Video A Survey <s> Analysis of audio and music <s> In the speech technology research community there is an increasing trend to use open source solutions. We present a new tool in that spirit, WaveSurfer, which has been developed at the Centre for Speech Technology at KTH. It has been designed for tasks such as viewing, editing, and labeling of audio data. WaveSurfer is built around a small core to which most functionality is added in the form of plug-ins. The tool has been designed to work on most common platforms and with the aims that it should be easy to configure and extend. WaveSurfer is provided as open source, under the GPL license with the explicit goal that the speech community jointly will improve and expand its scope and capabilities. <s> BIB001 </s> Tools for Searching, Annotation and Analysis of Speech, Music, Film and Video A Survey <s> Analysis of audio and music <s> We present MATCH, a toolkit for aligning audio recordings of different renditions of the same piece of music, based on an efficient implementation of a dynamic time warping algorithm. A forward path estimation algorithm constrains the alignment path so that dynamic time warping can be performed with time and space costs that are linear in the size of the audio files. Frames of audio are represented by a positive spectral difference vector, which emphasises note onsets in the alignment process. In tests with Classical and Romantic piano music, the average alignment error was 41ms (median 20ms), with only 2 out of 683 test cases failing to align. The software is useful for content-based indexing of audio files and for the study of performance interpretation; it can also be used in real-time for tracking live performances. The toolkit also provides functions for displaying the cost matrix, the forward and backward paths, and any metadata associated with the recordings, which can be shown in real time as the alignment is computed. <s> BIB002
Analyses which focus on acoustic properties, in phonetics and music, regularly make use of tools which employ Fourier analysis or other methods such as auto-correlation to determine the component frequencies of a signal and their relative strengths. In the case of non-static sounds, this information is most commonly presented in a sonogram (a 2 1/2-dimensional display with time on the horizontal axis, frequency on the vertical axis, and amplitude or intensity shown by different gradations of colour, or a grey-scale). Many such tools exist to effect such analysis: Wavesurfer BIB001 ) is a good example of software from the research community, while Matlab (with its Signal Processing toolbox (The MathWorks, 1994 ) is probably the most commonly used commercial software. Musicians use such tools for many purposes, including the analysis of instrumental tone (e.g.,  and the analysis of pitch articulations and vibrato in performance  . Analysing musical performance has become a topic for research, spurred by the two factors of a now substantial history of recorded music and tools to facilitate the analysis of music-as-sound. However, there are still considerable gaps between the information which software can derive from musical sound and the information which researchers want to discover. For example, it is rarely a simple and straightforward matter to distinguish where notes begin and end in a sonogram, and while the frequency composition of a sound can be derived, that does not always correlate simply with its perceived pitch composition. The most effective use of ICT in this area, therefore, comes when software allows the researcher to bring to play more effectively or more rapidly his or her musical ear and judgement. One example is MATCH BIB002  , which aligns two performances of the same piece, allowing a researcher to quickly and easily compare how two performers treat the same passage of the piece.