Abstract
This paper presents the Gene Fragment Competition concept that can be used with Hybrid Genetic Algorithms specially in signal and image processing. Memetic Algorithms have shown great success in real-life problems by adding local search operators to improve the quality of the already achieved "good" solutions during the evolutionary process. Nevertheless these traditional local search operators don't perform well in highly demanding evaluation processes. This stresses the need for a new semi-local non-exhaustive method. Our proposed approach sits as a tradeoff between classical Genetic Algorithms and traditional Memetic Algorithms, performing a quasi-global/quasi-local search by means of gene fragment evaluation and selection. The applicability of this hybrid Genetic Algorithm to the signal processing problem of Polyphonic Music Transcription is shown. The results obtained show the feasibility of the approach.

Abstract
Perceptual audio coders rely on the efficient reduction of perceptually irrelevant components of the audio signal as well as on the removal of statistical signal redundancies to achieve good coding gains. In order to reach high compression ratios without reducing the subjective quality of the encoded audio signal, it is necessary to identify critically interdependent functional units of the encoding algorithm and to jointly optimize their performance. A flexible and interactive simulation and analysis environment has been programmed to assist the development and optimization of a new perceptual audio coder. The main features of this environment will be explained and the most relevant aspects that were found to limit the encoding performance will be presented.

Abstract
This paper describes a method for automatically assessing the quality of manufactured roof-tiles using digital audio signal processing and pattern recognition techniques. A prototype system has been developed that is based on a mixed PC/DSP platform, where the real-time constraint is one of the main key issues. The suitability of the classification process for implementation in an industrial environment is also addressed.

Abstract
This paper presents several improvements that have been introduced to the design and operation of an adaptive 20-band room equalizer. The equalizer is implemented on a TMS320C6711 DSP platform and performs fast FIR filtering in the frequency domain. In order to reach fast adaptation to time-varying acoustic conditions, several adaptation rules operating in the frequency domain have been evaluated and the impact of a frequency-varying stepsize parameter on the convergence rate has been studied. These results will be presented along with ideas and plans for future developments.

Abstract
In the application of conventional audio compression algorithms to low bit rate audio coding one is faced with the unsatisfactory tradeoff between coarser quantization and audio bandwidth reduction. Frequency Extension has therefore emerged as an important tool for the satisfactory performance of low bit rate audio codecs. In this paper we describe one of a newer class of Frequency Extension techniques which are applied directly to the high frequency resolution representation of the signal (e.g., MDCT). This particular technique is based on a Fractal Self-Similarity Model (FSSM) for the short-term frequency representation of the signal. The FSSM model, which may include multiple dilation and translation terms, has been found to be effective for a wide variety of speech and music signals and provides a compact description for long term correlation that may exist in frequency domain. The high frequency resolution of MDCT aids in accurate parameter estimation for the model, which in turn has shown promise as a Frequency Extension tool that offers a detailed and natural sounding quality at low bit rates. Structure of the FSSM model, issues related to parameter estimation, and its application to audio coding for bit rates of 8-48 kbps is discussed. Audio demos are available at http://www.atc-labs.com/fssm.

Abstract
This paper presents a new method to the adaptive cancellation of acoustic feedbacks. The method uses high resolution frequency analysis and high-Q notch filters so as to accurately detect feedbacks and cancel them without disturbing noticeably the main audio spectrum. The method will be described, its implementation on a TMS320C6711 DSP platform for real time operation will be explained, and results for the adaptive cancellation of two simultaneous acoustic feedbacks will be presented.