Sound morphing is a transformation that gradually blurs the distinction between the source and target sounds. For musical instrument sounds, the morph must operate across timbre dimensions to create the auditory illusion of hybrid musical instruments. The ultimate goal of sound morphing is to perform perceptually linear transitions, which requires an appropriate model to represent the sounds being morphed and an interpolation function to obtain intermediate sounds. Typically, morphing techniques directly interpolate the parameters of the sound model without considering the perceptual impact or evaluating the results. Perceptual evaluations are cumbersome and not always conclusive. In this work, we seek parameters of a sound model that favor linear variation of perceptually motivated temporal and spectral features used to guide the morph towards more perceptually linear results. The requirement of linear variation of feature values gives rise to objective evaluation criteria for sound morphing. We investigate several spectral envelope morphing techniques to determine which spectral representation renders the most linear transformation in the spectral shape feature domain. We found that interpolation of line spectral frequencies gives the most linear spectral envelope morphs. Analogously, we study temporal envelope morphing techniques and we concluded that interpolation of cepstral coefficients results in the most linear temporal envelope morph.

The model used to represent musical instrument sounds plays a crucial role in the quality of sound transformations. Ideally, the representation should be compact and accurate, while its parameters should give flexibility to independently manipulate perceptually related features of the sounds. This work describes a source-filter model for musical instrument sounds based on the sinusoidal plus residual decomposition. The sinusoidal component is modeled as sinusoidal partial tracks (source) and a time-varying spectral envelope (filter), and the residual is represented as white noise (source) shaped by a time-varying spectral envelope (filter). This article presents estimation and representation techniques that give totally independent and intuitive control of the spectral envelope model and the frequencies of the partials to perform perceptually related sound transformations. The result of a listening test confirmed that, in general, the sounds resynthesized from the source-filter model are perceptually similar to the original recordings.

The goal of sound morphing by feature interpolation is to obtain sounds whose values of features are intermediate between those of the source and target sounds. In order to do this, we should be able to resynthesize sounds that present a set of predefined feature values, a notoriously difficult problem. In this work, we present morphing techniques to obtain hybrid musical instrument sounds whose feature values correspond as close as possible to the ideal interpolated values. When the features capture perceptually relevant information, the morphed sound whose features are interpolated is perceptually intermediate. The features we use are acoustic correlates of salient timbre dimensions derived from perceptual studies, such that sounds whose feature values are intermediate between two would be placed between them in the underlying timbre space. We measure the perceptual impact of the morphed sounds directly by the feature values, using them as an objective measure with which to evaluate the results. Thus we consider that the morphed sounds change perceptually linearly when the corresponding feature values vary linearly.

The amplitude modulations of musical instrument sounds and speech are important perceptual cues. Accurate estimation of the amplitude, or equivalently energy, envelope of a time-domain signal (waveform) is not a trivial task, though. Ideally, the amplitude envelope should outline the waveform connecting the main peaks and avoiding over fitting. In this work we propose a method to obtain a smooth function that approximately matches the main peaks of the waveform using true envelope estimation, dubbed true amplitude envelope. True envelope is a cepstral smoothing technique that has been shown to outperform traditional envelope estimation techniques both in accuracy of estimation and ease of order selection. True amplitude envelope gives a reliable estimation that follows closely sudden variations in amplitude and avoids ripples in more stable regions with near optimal order selection depending on the fundamental frequency of the signal.