Download Adaptive Pitch-Shifting With Applications to Intonation Adjustment in a Cappella Recordings A central challenge for a cappella singers is to adjust their intonation and to stay in tune relative to their fellow singers. During
editing of a cappella recordings, one may want to adjust local intonation of individual singers or account for global intonation drifts
over time. This requires applying a time-varying pitch-shift to the
audio recording, which we refer to as adaptive pitch-shifting. In
this context, existing (semi-)automatic approaches are either laborintensive or face technical and musical limitations. In this work,
we present automatic methods and tools for adaptive pitch-shifting
with applications to intonation adjustment in a cappella recordings. To this end, we show how to incorporate time-varying information into existing pitch-shifting algorithms that are based on
resampling and time-scale modification (TSM). Furthermore, we
release an open-source Python toolbox, which includes a variety
of TSM algorithms and an implementation of our method. Finally,
we show the potential of our tools by two case studies on global
and local intonation adjustment in a cappella recordings using a
publicly available multitrack dataset of amateur choral singing.
Download A Corpus-Driven Parametric Modal Reverberator A parametric modal reverberator is presented in which synthesis parameters are derived from a large, curated corpus of room impulse responses (IRs). The collected responses are subjected to modal decomposition, yielding per-mode frequencies, damping coefficients, and residue amplitudes, together with a short early-reflection finite impulse response (FIR) filter. From the decomposed data, a feature table is constructed per IR comprising standard acoustic indices, per-band damping and density statistics, amplitude distributions, and FIR descriptors—50 variables in total. Six acoustically meaningful user controls are selected; since these exhibit substantial pairwise correlations across the corpus, they are orthogonalised via principal component analysis (PCA) prior to regression.
Download Unsupervised Audio Key and Chord Recognition This paper presents a new methodology for determining chords of a music piece without using training data. Specifically, we introduce: 1) a wavelet-based audio denoising component to enhance a chroma-based feature extraction framework, 2) an unsupervised key recognition component to extract a bag of local keys, 3) a chord recognizer using estimated local keys to adjust the chromagram based on a set of well-known tonal profiles to recognize chords on a frame-by-frame basis. We aim to recognize 5 classes of chords (major, minor, diminished, augmented, suspended) and 1 N (no chord or silence). We demonstrate the performance of the proposed approach using 175 Beatles’ songs which we achieved 75% in F-measure for estimating a bag of local keys and at least 68.2% accuracy on chords without discarding any audio segments or the use of other musical elements. The experimental results also show that the wavelet-based denoiser improves the chord recognition rate by approximately 4% over that of other chroma features.
Download State of the Art in Sound Texture Synthesis The synthesis of sound textures, such as rain, wind, or crowds, is an important application for cinema, multimedia creation, games and installations. However, despite the clearly defined requirments of naturalness and flexibility, no automatic method has yet found widespread use. After clarifying the definition, terminology, and usages of sound texture synthesis, we will give an overview of the many existing methods and approaches, and the few available software implementations, and classify them by the synthesis model they are based on, such as subtractive or additive synthesis, granular synthesis, corpus-based concatenative synthesis, wavelets, or physical modeling. Additionally, an overview is given over analysis methods used for sound texture synthesis, such as segmentation, statistical modeling, timbral analysis, and modeling of transitions. 2
Download Time Scale Modification of Audio Using Non-Negative Matrix Factorization This paper introduces an algorithm for time-scale modification of audio signals based on using non-negative matrix factorization. The activation signals attributed to the detected components are used for identifying sound events. The segmentation of these events is used for detecting and preserving transients. In addition, the algorithm introduces the possibility of preserving the envelopes of overlapping sound events while globally modifying the duration of an audio clip.
Download Audio Transport: A Generalized Portamento via Optimal Transport This paper proposes a new method to interpolate between two audio signals. As an interpolation parameter is changed, the pitches in one signal slide to the pitches in the other, producing a portamento, or musical glide. The assignment of pitches in one sound to pitches in the other is accomplished by solving a 1-dimensional optimal transport problem. In addition, we introduce several techniques that preserve the audio fidelity over this highly nonlinear transformation. A portamento is a natural way for a musician to transition between notes, but traditionally it has only been possible for instruments with a continuously variable pitch like the human voice or the violin. Audio transport extends the portamento to any instrument, even polyphonic ones. Moreover, the effect can be used to transition between different instruments, groups of instruments, or any other pair of audio signals. The audio transport effect operates in real-time; we provide an open-source implementation. In experiments with sinusoidal inputs, the interpolating effect is indistinguishable from ideal sine sweeps. More generally, the effect produces clear, musical results for a wide variety of inputs.
Download Optimization of audio graphs by resampling Interactive music systems are dynamic real-time systems which combine control and signal processing based on an audio graph. They are often used on platforms where there are no reliable and precise real-time guarantees. Here, we present a method of optimizing audio graphs and finding a compromise between audio quality and gain in execution time by downsampling parts of the graph. We present models of quality and execution time and we evaluate the models and our optimization algorithm experimentally.
Download Timpani Drum Synthesis in 3D on GPGPUs Physical modeling sound synthesis for systems in 3D is a computationally intensive undertaking; the number of degrees of freedom is very large, even for systems and spaces of modest physical dimensions. The recent emergence into the mainstream of highly parallel multicore hardware, such as general purpose graphical processing units (GPGPUs) has opened an avenue of approach to synthesis for such systems in a reasonable amount of time, without severe model simplification. In this context, new programming and algorithm design considerations appear, especially the ease with which a given algorithm may be parallelized. To this end finite difference time domain methods operating over regular grids are explored, with regard to an interesting and non-trivial test problem, that of the timpani drum. The timpani is chosen here because its sounding mechanism relies on the coupling between a 2D resonator and a 3D acoustic space (an internal cavity). It is also of large physical dimensions, and thus simulation is of high computational cost. A timpani model is presented, followed by a brief presentation of finite difference time domain methods, followed by a discussion of parallelization on GPGPU, and simulation results.
Download Real-Time Modal Synthesis of Crash Cymbals with Nonlinear Approximations, Using a GPU We apply modal synthesis to create a virtual collection of crash cymbals. Synthesizing each cymbal may require enough modes to stress a modern CPU, so a full drum set would certainly not be tractable in real-time. To work around this, we create a GPU-accelerated modal filterbank, with each individual set piece allocated over two thousand modes. This takes only a fraction of available GPU floating-point throughput. With CPU resources freed up, we explore methods to model the different instrument response in the linear/harmonic and non-linear/inharmonic regions that occur as more energy is present in a cymbal: a simple approach, yet one that preserves the parallelism of the problem, uses multisampling, and a more physically-based approach approximates modal coupling.
Download Joint Estimation of Fader and Equalizer Gains of DJ Mixers Using Convex Optimization Disc jockeys (DJs) use audio effects to make a smooth transition from one song to another. There have been attempts to computationally analyze the creative process of seamless mixing. However, only a few studies estimated fader or equalizer (EQ) gains controlled by DJs. In this study, we propose a method that jointly estimates time-varying fader and EQ gains so as to reproduce the mix from individual source tracks. The method approximates the equalizer filters with a linear combination of a fixed equalizer filter and a constant gain to convert the joint estimation into a convex optimization problem. For the experiment, we collected a new DJ mix dataset that consists of 5,040 real-world DJ mixes with 50,742 transitions, and evaluated the proposed method with a mix reconstruction error. The result shows that the proposed method estimates the time-varying fader and equalizer gains more accurately than existing methods and simple baselines.