Abstract
The accurate estimation of the frequency of sinusoids is a frequent problem in many signal processing problems including the real-time analysis of the singing voice. In this paper we rely on a single DFT magnitude spectrum in order to perform frequency estimation in a non-iterative way. Two new frequency estimation methods are derived that are matched to the time analysis window and that reduce the maximum absolute estimation error to about 0.1% of the bin width of the DFT. The performance of these methods is evaluated including the parabolic method as a reference, and considering the influence of noise. A combined model is proposed that offers higher noise robustness than that of a single model. ©2010 IEEE.

Abstract
A new DSP laboratory course has been included in the Electrical and Computer Engineering curriculum at the Faculdade de Engenharia da Universidade do Porto, in Portugal, since the school year of 1999/2000. This paper addresses the context and motivation underlying this new course, outlines its structure and methodology, highlights the design and goals of all DSP experiments currently proposed for the 13 weeks of the semester, and reports on the receptivity students have expressed to this elective course. The course is based on the TI C31 Starter Kit and tries to combine full use of its resources with a representative diversity of efficient digital signal processing techniques and associated application scenarios. A perspective is also given on current plans to reinforce DSP expertise at the graduate level.

Abstract
This paper presents a new method for multiple fundamental frequency (F0) estimation on piano recordings. We propose a framework based on a genetic algorithm in order to analyze the overlapping overtones and search for the most likely F0 combination. The search process is aided by adaptive spectral envelope modeling and dynamic noise level estimation: while the noise is dynamically estimated, the spectral envelope of previously recorded piano samples (internal database) is adapted in order to best match the piano played on the input signals and aid the search process for the most likely combination of F0s. For comparison, several state-of-the-art algorithms were run across various musical pieces played by different pianos and then compared using three different metrics. The proposed algorithm ranked first place on Hybrid Decay/Sustain Score metric, which has better correlation with the human hearing perception and ranked second place on both onset-only and onset-offset metrics. A previous genetic algorithm approach is also included in the comparison to show how the proposed system brings significant improvements on both quality of the results and computing time. Index Terms-Acoustic signal analysis, automatic

Abstract
Recent research in high-quality audio coding seeks not only improved coding gains but also new functionalities, such as easy semantic access to compressed audio material and audio modification in the compressed domain. These objectives imply the decomposition of the audio signal into several components of specific semantic value, such as sinusoidal components, that take advantage of selective coding and parametrization tools. In this paper we presume an MDCT based audio coding environment and present a new technique combining spectral envelope normalization with accurate subtraction of sinusoidal components in the MDCT frequency domain. It is shown how a parametrization of L stationary sinusoids in the complex ODFT spectrum can lead to the effective subtraction in the real MDCT spectrum, of 3L spectral lines. A demonstration of the implementation of the technique is available on the Internet.

Abstract
This paper addresses the extraction of parametric information in an audio coder that uses the MDCT filter bank. The computation of the filter bank is reformulated as a function of the Odd-DFT, in order to allow the estimation of the frequency, the phase and the magnitude of stationary sinusoids. Closed expression delivering accurate estimates are derived and explained, and their implementation and accuracy are illustrated in a Web page that includes a demonstration Matlab M-file.

Abstract
Perceptual coders have proven to be highly efficient in the context of audio or video applications involving bit rate reduction. However, this efficiency is strongly limited in very low bit rate coding conditions. This paper studies the multiplicative effects of quantization in the frequency domain, when an overlapped filter bank (TDAC) is used to shape the quantization noise in a perceptually optimal way. The associated circular convolution operation generates aliased components in the time domain that are examined and subjected to minimization. A closed form expression is suggested to approximate an optimal transform window offering a desired tradeoff between the reduction of the time artifacts produced by a coarse quantization and the reduction of the stop-band leakage, relative to other transform windows commonly used.