Since the MIDI 1.0 specification [1], well over 15 years ago, many have been the attempts to give a solution to all the limitations that soon became clear. None of these have had a happy ending, mainly due to commercial interests and as a result, when trying to find an appropriate synthesis control user interface, we had not many choices but the use of MIDI. That’s the reason why the idea of defining a new user interface aroused. In this article, the main components of this interface will be discussed, paying special attention to the advantages and new features it reports to the enduser.

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Periodic or quasi-periodic low-frequency components (i.e. vibrato and tremolo) are present in steadystate portions of sustained instrumental sounds. If we are interested both in studying its expressive meaning, or in building a hierarchical multi-level representation of sound in order to manipulate it and transform it with musical purposes those components should be isolated and separated from the amplitude and frequency envelopes. Within the SMS analysis framework it is now feasible to extract high level time-evolving attributes starting from basic analysis data. In the case of frequency envelopes we can apply STFTs to them, then check if there is a prominent peak in the vibrato/tremolo range and, if it is true, we can smooth it away in the frequency domain; finally, we can apply an IFFT to each frame in order to re-construct an envelope that has been cleaned of those quasi-periodic low-frequency components. Two important problems nevertheless have to be tackled, and ways of overcoming them will be discussed in this paper: first, the periodicity of vibrato and tremolo, that is quite exact only when the performers are professional musicians; second: the interactions between formants and fundamental frequency trajectories, that blur the real tremolo component and difficult its analysis.

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The basic Spectral Modeling Synthesis (SMS) technique models sounds as the sum of sinusoids plus a residual. Though this analysis/synthesis system has proved to be successful in transforming sounds, more powerful and intuitive musical transformations can be achieved by moving into the SMS high-level attribute plane. In this paper we describe how to extract high level sound attributes from the basic representation, modify them, and add them back before the synthesis stage. In this process new problems come up for which we propose some initial solutions.

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In this paper, we propose a computer software for modifying rhythmic performances of polyphonic musical audio signals. It first describes the rhythmic content of an audio signal (i.e. determination of tempi and beat indexes at the quarter-note and eighth-note levels, as well as estimation of the swing ratio). Then, the signal is transformed in real-time using a time-stretch algorithm. We present basic techniques provided by commercial products for swing modification and compare these to our system.

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This paper presents a new approach on transforming a modal voice into a rough or growl voice. The goal of such transformations is to be able to enhance voice expressiveness in singing voice productions. Both techniques work with spectral models and are based on adding sub-harmonics in frequency domain to the original input voice spectrum.

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This paper introduces a method to transform voice based on modeling the radiated voice pulses in frequency domain. This approach tries to combine the strengths of classical time and frequency domain techniques into a single framework, providing both an independent control of each voice pulse and flexible timbre and phase modification capabilities.

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In this paper we address the expressive control of singing voice synthesis. Singing Voice Synthesizers (SVS) traditionally require two types of inputs: a musical score and lyrics. The musical expression is then typically either generated automatically by applying a model of a certain type of expression to a high-level musical score, or achieved by manually editing low-level synthesizer parameters. We propose an alternative method, where the expression control is derived from a singing performance. In a first step, an analysis module extracts expressive information from the input voice signal, which is then adapted and mapped to the internal synthesizer controls. The presented implementation works in an off-line manner processing user input voice signals and lyrics using a phonetic segmentation module. The main contribution of this approach is to offer a direct way of controlling the expression of SVS. The further step is to run the system in real-time. The last section of this paper addresses a possible strategy for real-time operation.

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The ability of a sound synthesizer to provide realistic sounds depends to a great extent on the availability of expressive controls. One of the most important expressive features a user of the synthesizer would desire to have control of, is timbre. Timbre is a complex concept related to many musical indications in a score such as dynamics, accents, hand position, string played, or even indications referring timbre itself. Musical indications are in turn related to low level performance controls such as bow velocity or bow force. With the help of a data acquisition system able to record sound synchronized to performance controls and aligned to the performed score and by means of statistical analysis, we are able to model the interrelations among sound (timbre), controls and musical score indications. In this paper we present a procedure for score-controlled timbre transformations of violin sounds within a sample based synthesizer. Given a sound sample and its trajectory of performance controls: 1) a transformation of the controls trajectory is carried out according to the score indications, 2) a new timbre corresponding to the transformed trajectory is predicted by means of a timbre model that relates timbre with performance controls and 3) the timbre of the original sound is transformed by applying a timevarying filter calculated frame by frame as the difference of the original and predicted envelopes.

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In this paper we propose a method to estimate and transform harmonic components in wide-band conditions, out of a single period of the analyzed signal. This method allows estimating harmonic parameters with higher temporal resolution than typical Short Time Fourier Transform (STFT) based methods. We also discuss transformations and synthesis strategies in such context, focusing on the human voice.

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In many applications of sound transformation, such as sound design, mixing, mastering, and composition the user interactively searches for appropriate parameters. However, automatic applications of sound transformation, such as mosaicing, may require choosing parameters without user intervention. When the target can be specified by its synthesis context, or by example (from features of the example), “adaptive effects” can provide such control. But there exist few general strategies for building adaptive effects from arbitrary sets of transformations and descriptor targets. In this study, we decouple the usually direct link between analysis and transformation in adaptive effects, attempting to include more diverse transformations and descriptors in adaptive transformation, if at the cost of additional complexity or difficulty. We build an analytic model of a deliberately simple transformation-descriptor (TD) domain, and show some preliminary results.

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