Systems for sound retrieval are usually "sourcecentred ". This means that retrieval is based on using the proper keywords that define or specify a sound source. Although this type of description is of great interest, it is very difficult to implement it into realistic automatic labelling

, and loudness. I Subjective features: describing the sounds using personal descriptive language. This requires training the system (in our case, by example) to understand the meaning of these descriptive terms. For example, a user might be looking for a “shimmering ” sound.

by Schaeffer under the name morphological description. Part of this description consists in describing a sound by identifying the temporal evolution of its acoustic properties to a set of profiles. In this work, we consider three morphological descriptions: dynamic profiles (ascending, descending, ascending

in a low-Earth orbit, provided a wealth of data which was used to test this concept and the accuracy of the retrievals. Several investigations have already demonstrated that he retrieval accuracies obtained with GPS/MET is already comparable, if not better, than the more traditional atmospheric sensing

We present an approach to model the temporal evolution of audio descriptors using Segmental Models (SMs). This method yields a signal segmentation into a sequence of primitives, constituted by a set of user-defined trajectories. This allows one to consider specific primitive shapes, model

This report presents a detailed analysis and review of NLP evaluation, in principle and in practice. Part 1 examines evaluation concepts and establishes a framework for NLP system evaluation. This makes use of experience in the related area of information retrieval and the analysis also refers

). Basically is generates the correct timing signals needed and shifts through a 16-bit word one bit at a time (monochrome) for pixel information. As data is requested, SDRAM memory is accessed and data is retrieved. Accessing SDRAM memory may sound easy, but it’s more complicated than SRAM. XESS has produced

and reasoned with, using a single reasoning procedure. We establish soundness, completeness, and termination of the reasoning procedure. Detailed explanations and examples are included to describe the proposed completion rules.

compute it. Basically, timbric and rhythmic description of audio is used for this purpose. From our point of view, some of these descriptors have been designed under some rigid constrains and the generalization of these algorithms into more flexible applications becomes a difficult task. In this paper, we

Shape description is one of the key parts of image content description for image retrieval. Most of existing shape descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. In this paper, a generic Fourier descriptor (GFD) is proposed