In this paper, analysis and trans-synthesis of acoustic bowed string instrument recordings with new non-negative matrix factorization (NMF) procedure are presented. This work shows that it may require more than one template to represent a note according to time-varying behavior of timbre, especially played by bowed string instruments. The proposed method improves original NMF without the knowledge of tone models and the number of required templates in advance. Resultant NMF information is then converted into the synthesis parameters of the sinusoidal synthesis. Bach cello suites recorded by Fournier and Starker are used in the experiments. Analysis and trans-synthesis examples of the recordings are also provided. Index Terms—trans-synthesis, non-negative matrix factorization, bowed string instrument

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Sound field simulation is widely used for acoustic design; however, this simulation needs many computational resources. On the other hand, FPGA becomes major for acceleration. To take advantage of hardware acceleration by FPGA, hardware oriented algorithm which consumes small number of gates and memory is necessary. This paper addresses hardware acceleration of sound field simulation using FPGA. Improved Digital Huygens Model (DHM) for hardware is implemented and speed up ratio is examined. For 2D simulation, the implemented accelerator is 1,170 times faster than software simulation. For 3D simulation, it is shown that FDTD based method is suitable for hardware implementation and required hardware resource are estimated.

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In this paper we evaluate some of the alternative methods commonly applied in the first stages of the signal processing chain of automatic melody extraction systems. Namely, the first two stages are studied – the extraction of sinusoidal components and the computation of a time-pitch salience function, with the goal of determining the benefits and caveats of each approach under the specific context of predominant melody estimation. The approaches are evaluated on a data-set of polyphonic music containing several musical genres with different singing/playing styles, using metrics specifically designed for measuring the usefulness of each step for melody extraction. The results suggest that equal loudness filtering and frequency/amplitude correction methods provide significant improvements, whilst using a multi-resolution spectral transform results in only a marginal improvement compared to the standard STFT. The effect of key parameters in the computation of the salience function is also studied and discussed.

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Research into sparse atomic models has recently intensified in the image and audio processing communities. While other reviews exist, we believe this paper provides a good starting point for the uninitiated reader as it concisely summarizes the state-of-the-art, and presents most of the major topics in an accessible manner. We discuss several approaches to the sparse approximation problem including various greedy algorithms, iteratively re-weighted least squares, iterative shrinkage, and Bayesian methods. We provide pseudo-code for several of the algorithms, and have released software which includes fast dictionaries and reference implementations for many of the algorithms. We discuss the relevance of the different approaches for audio applications, and include numerical comparisons. We also illustrate several audio applications of sparse atomic modeling.

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An efficient and perfectly invertible signal transform featuring a constant-Q frequency resolution is presented. The proposed approach is based on the idea of the recently introduced nonstationary Gabor frames. Exploiting the properties of the operator corresponding to a family of analysis atoms, this approach overcomes the problems of the classical implementations of constant-Q transforms, in particular, computational intensity and lack of invertibility. Perfect reconstruction is guaranteed by using an easy to calculate dual system in the synthesis step and computation time is kept low by applying FFT-based processing. The proposed method is applied to real-life signals and evaluated in comparison to a related approach, recently introduced specifically for audio signals.

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This paper presents an extension to the dual-window-length Real-Time Iterative Spectrogram Inversion phase estimation algorithm (RTISI). Instead of a transient detection in advance, the phase estimator itself determines the correct window length when the phase information for all window lengths have already been estimated. This way, we get significant improvements compared with the previous method. Additionally, we extend this estimator to configurations with three or more window lengths.

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We present an algorithm for sound analysis and resynthesis with local automatic adaptation of time-frequency resolution. There exists several algorithms allowing to adapt the analysis window depending on its time or frequency location; in what follows we propose a method which select the optimal resolution depending on both time and frequency. We consider an approach that we denote as analysis-weighting, from the point of view of Gabor frame theory. We analyze in particular the case of different adaptive timevarying resolutions within two complementary frequency bands; this is a typical case where perfect signal reconstruction cannot in general be achieved with fast algorithms, causing a certain error to be minimized. We provide examples of adaptive analyses of a music sound, and outline several possibilities that this work opens.

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Cross modulation or Exponential FM is a sound synthesis technique associated with modular analog subtractive synthesizers. It differs from the more well-known linear FM synthesis technique in that the modulation is an exponential function of the control voltage. Its spectrum shape is more complex, thus giving it a larger bandwidth with respect to the modulation depth. Thus, the prevention of aliasing distortion requires different conditions than Carson’s rule as used with linear FM. A suitable equation will be presented in this paper.

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In this paper we discuss the development of ontological representations of digital audio effects and provide a framework for the description of digital audio effects and audio effect transformations. After a brief account on our current research in the field of highlevel semantics for music production using Semantic Web technologies, we detail how an Audio Effects Ontology can be used within the context of intelligent music production tools, as well as for musicological purposes. Furthermore, we discuss problems in the design of such an ontology arising from discipline-specific classifications, such as the need for encoding different taxonomical systems based on, for instance, implementation techniques or perceptual attributes of audio effects. Finally, we show how information about audio effect transformations is represented using Semantic Web technologies, the Resource Description framework (RDF) and retrieved using the SPARQL query language.

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Gabor Multipliers are signals operator which are diagonal in a time-frequency representation of signals and can be viewed as timefrequency transfer function. If we estimate a Gabor mask between a note played by two instruments, then we have a time-frequency representation of the difference of timbre between these two notes. By averaging the energy contained in the Gabor mask, we obtain a measure of this difference. In this context, our goal is to automatically localize the time-frequency regions responsible for such a timbre dissimilarity. This problem is addressed as a feature selection problem over the time-frequency coefficients of a labelled data set of sounds.

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