TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer

In this work, we address the problem of musical timbre transfer, where the goal is to manipulate the timbre of a sound sample from one instrument to match another instrument while preserving other musical content, such as pitch, rhythm, and loudness. In principle, one could apply image-based style transfer techniques to a time-frequency representation of an audio signal, but this depends on having a representation that allows independent manipulation of timbre as well as high-quality waveform generation. We introduce TimbreTron, a method for musical timbre transfer which applies "image" domain style transfer to a time-frequency representation of the audio signal, and then produces a high-quality waveform using a conditional WaveNet synthesizer. We show that the Constant Q Transform (CQT) representation is particularly well-suited to convolutional architectures due to its approximate pitch equivariance. Based on human perceptual evaluations, we confirmed that TimbreTron recognizably transferred the timbre while otherwise preserving the musical content, for both monophonic and polyphonic samples.Comment: 17 pages, published as a conference paper at ICLR 201

Exploiting Compositionality to Explore a Large Space of Model Structures

The recent proliferation of richly structured probabilistic models raises the question of how to automatically determine an appropriate model for a dataset. We investigate this question for a space of matrix decomposition models which can express a variety of widely used models from unsupervised learning. To enable model selection, we organize these models into a context-free grammar which generates a wide variety of structures through the compositional application of a few simple rules. We use our grammar to generically and efficiently infer latent components and estimate predictive likelihood for nearly 2500 structures using a small toolbox of reusable algorithms. Using a greedy search over our grammar, we automatically choose the decomposition structure from raw data by evaluating only a small fraction of all models. The proposed method typically finds the correct structure for synthetic data and backs off gracefully to simpler models under heavy noise. It learns sensible structures for datasets as diverse as image patches, motion capture, 20 Questions, and U.S. Senate votes, all using exactly the same code.United States. Army Research Office (ARO grant W911NF-08-1-0242)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Treatment success for overactive bladder with urinary urge incontinence refractory to oral antimuscarinics: a review of published evidence

<p>Abstract</p> <p>Background</p> <p>Treatment options for overactive bladder (OAB) with urinary urge incontinence (UUI) refractory to oral antimuscarinics include: botulinum toxin type A (BoNTA), sacral neuromodulation (SNM), and augmentation cystoplasty (AC). A standard treatment success metric that can be used in both clinical and economic evaluations of the above interventions has not emerged. Our objective was to conduct a literature review and synthesis of published measures of treatment success for OAB with UUI interventions and to identify a treatment success outcome.</p> <p>Methods</p> <p>We performed a literature review of primary studies that used a definition of treatment success in the OAB with UUI population receiving BoNTA, SNM, or AC. The recommended success outcome was compared to generic and disease-specific health-related quality-of-life (HRQoL) measures using data from a BoNTA treatment study of neurogenic incontinent patients.</p> <p>Results</p> <p>Across all interventions, success outcomes included: complete continence (n = 23, 44%), ≥ 50% improvement in incontinence episodes (n = 16, 31%), and subjective improvement (n = 13, 25%). We recommend the OAB with UUI treatment success outcome of ≥ 50% improvement in incontinence episodes from baseline. Using data from a neurogenic BoNTA treatment study, the average change in the Incontinence Quality of Life questionnaire was 8.8 (95% CI: -4.7, 22.3) higher for those that succeeded (N = 25) versus those that failed (N = 26). The average change in the SF-6D preference score was 0.07 (95% CI: 0.02, 0.12) higher for those that succeeded versus those that failed.</p> <p>Conclusion</p> <p>A treatment success definition that encompasses the many components of underlying OAB with UUI symptoms is currently not practical as a consequence of difficulties in measuring urgency. The treatment success outcome of ≥ 50% improvement in incontinence episodes was associated with a clinically meaningful improvement in disease-specific HRQoL for those with neurogenic OAB with UUI. The recommended success definition is less restrictive than a measure such as complete continence but includes patients who are satisfied with treatment and experience meaningful improvement in symptoms. A standardized measure of treatment success will be useful in clinical and health economic applications.</p