Search Results for author: Christopher Mitcheltree

Found 7 papers, 4 papers with code

Differentiable All-pole Filters for Time-varying Audio Systems

7 code implementations11 Apr 2024 Chin-Yun Yu, Christopher Mitcheltree, Alistair Carson, Stefan Bilbao, Joshua D. Reiss, György Fazekas

Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers.

Audio Effects Modeling Audio Synthesis

Modulation Extraction for LFO-driven Audio Effects

1 code implementation22 May 2023 Christopher Mitcheltree, Christian J. Steinmetz, Marco Comunità, Joshua D. Reiss

Low frequency oscillator (LFO) driven audio effects such as phaser, flanger, and chorus, modify an input signal using time-varying filters and delays, resulting in characteristic sweeping or widening effects.

SerumRNN: Step by Step Audio VST Effect Programming

1 code implementation8 Apr 2021 Christopher Mitcheltree, Hideki Koike

Learning to program an audio production VST synthesizer is a time consuming process, usually obtained through inefficient trial and error and only mastered after years of experience.

White-box Audio VST Effect Programming

1 code implementation5 Feb 2021 Christopher Mitcheltree, Hideki Koike

Learning to program an audio production VST plugin is a time consuming process, usually obtained through inefficient trial and error and only mastered after extensive user experience.

Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles

no code implementations NAACL 2018 Christopher Mitcheltree, Skyler Wharton, Avneesh Saluja

Users often wish to survey reviews or review snippets from the perspective of a certain aspect, which has resulted in a large body of work on aspect identification and extraction from such corpora.

Aspect Extraction

Barcodes for Medical Image Retrieval Using Autoencoded Radon Transform

no code implementations16 Sep 2016 Hamid. R. Tizhoosh, Christopher Mitcheltree, Shujin Zhu, Shamak Dutta

Using images in a training dataset, we autoencode Radon projections to perform binarization on outputs of hidden layers.

Binarization Medical Image Retrieval +2

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