652 citations · 1k across the 14 of their papers we have counts for
14 papers
Leveraging Neural Representations for Audio Manipulation
Scott H. Hawley, Christian J. Steinmetz
We investigate applying audio manipulations using pretrained neural network-based autoencoders as an alternative to traditional signal processing methods, since the former may prov…
ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan Drums
Scott H. Hawley, Andrew C. Morrison
We train an object detector built from convolutional neural networks to count interference fringes in elliptical antinode regions in frames of high-speed video recordings of transi…
Exploring Quality and Generalizability in Parameterized Neural Audio Effects
William Mitchell, Scott H. Hawley
Deep neural networks have shown promise for music audio signal processing applications, often surpassing prior approaches, particularly as end-to-end models in the waveform domain.…
SignalTrain: Profiling Audio Compressors with Deep Neural Networks
Scott H. Hawley, Benjamin Colburn, Stylianos I. Mimilakis
In this work we present a data-driven approach for predicting the behavior of (i.e., profiling) a given non-linear audio signal processing effect (henceforth "audio effect"). Our o…
Challenges for an Ontology of Artificial Intelligence
Scott H. Hawley
Of primary importance in formulating a response to the increasing prevalence and power of artificial intelligence (AI) applications in society are questions of ontology. Questions…
Visualizing Sound Directivity via Smartphone Sensors
Scott H. Hawley, Robert E. McClain
We present a fast, simple method for automated data acquisition and visualization of sound directivity, made convenient and accessible via a smartphone app, "Polar Pattern Plotter.…