activity
20132025
most citedHEAR: Holistic Evaluation of Audio Representations

36 citations · 60 across the 8 of their papers we have counts for

collaborators

8 papers

cs.HC2025

A Real-Time Gesture-Based Control Framework

Mahya Khazaei, Ali Bahrani, George Tzanetakis

We introduce a real-time, human-in-the-loop gesture control framework that can dynamically adapt audio and music based on human movement by analyzing live video input. By creating…

cs.HC2024★ 2 cited

Interactive Sonification for Health and Energy using ChucK and Unity

Yichun Zhao, George Tzanetakis

Sonification can provide valuable insights about data but most existing approaches are not designed to be controlled by the user in an interactive fashion. Interactions enable the…

cs.SD2022★ 36 cited

HEAR: Holistic Evaluation of Audio Representations

Joseph Turian, Jordie Shier, Humair Raj Khan +20

What audio embedding approach generalizes best to a wide range of downstream tasks across a variety of everyday domains without fine-tuning? The aim of the HEAR benchmark is to dev…

cs.SD2021★ 1 cited

One Billion Audio Sounds from GPU-enabled Modular Synthesis

Joseph Turian, Jordie Shier, George Tzanetakis +2

We release synth1B1, a multi-modal audio corpus consisting of 1 billion 4-second synthesized sounds, paired with the synthesis parameters used to generate them. The dataset is 100x…

cs.SD2020★ 3 cited

Deep Autotuner: a Pitch Correcting Network for Singing Performances

Sanna Wager, George Tzanetakis, Cheng-i Wang +1

We introduce a data-driven approach to automatic pitch correction of solo singing performances. The proposed approach predicts note-wise pitch shifts from the relationship between…

cs.SD2019★ 2 cited

Deep Autotuner: A Data-Driven Approach to Natural-Sounding Pitch Correction for Singing Voice in Karaoke Performances

Sanna Wager, George Tzanetakis, Cheng-i Wang +3

We describe a machine-learning approach to pitch correcting a solo singing performance in a karaoke setting, where the solo voice and accompaniment are on separate tracks. The prop…

cs.DC2017★ 9 cited

Espresso: Efficient Forward Propagation for BCNNs

Fabrizio Pedersoli, George Tzanetakis, Andrea Tagliasacchi

There are many applications scenarios for which the computational performance and memory footprint of the prediction phase of Deep Neural Networks (DNNs) needs to be optimized. Bin…

cs.LG2013★ 7 cited

The Orchive : Data mining a massive bioacoustic archive

Steven Ness, Helena Symonds, Paul Spong +1

The Orchive is a large collection of over 20,000 hours of audio recordings from the OrcaLab research facility located off the northern tip of Vancouver Island. It contains recorded…