50 citations · 75 across the 26 of their papers we have counts for
10 papers · 1 filter
Frequency-Aware Self-Supervised Music Representation Learning
Yicheng Gu, Junan Zhang, Jerry Li +2
Self-supervised learning (SSL) has emerged as an essential paradigm for music information retrieval (MIR). While current SSL models achieve state-of-the-art performance across vari…
Aliasing-Free Neural Audio Synthesis
Yicheng Gu, Junan Zhang, Chaoren Wang +3
In neural audio synthesis, neural vocoders and codecs are models that reconstruct waveforms from acoustic and latent representations, which are essential to the resulting audio qua…
Deep Regularized RNNs for Virtual Analog Modeling
V. Valtteri Kallinen, Lauri Juvela, Thom Sherson
Virtual analog (VA) modeling methods seek to emulate analog audio hardware using digital signal processing (DSP). Modeling approaches fall into three broad categories: white-box me…
Solid State Bus-Comp: A Large-Scale and Diverse Dataset for Dynamic Range Compressor Virtual Analog Modeling
Yicheng Gu, Runsong Zhang, Lauri Juvela +1
Virtual Analog (VA) modeling aims to simulate the behavior of hardware circuits via algorithms to replicate their tone digitally. Dynamic Range Compressor (DRC) is an audio process…
Neurodyne: Neural Pitch Manipulation with Representation Learning and Cycle-Consistency GAN
Yicheng Gu, Chaoren Wang, Zhizheng Wu +1
Pitch manipulation is the process of producers adjusting the pitch of an audio segment to a specific key and intonation, which is essential in music production. Neural-network-base…
Audio Codec Augmentation for Robust Collaborative Watermarking of Speech Synthesis
Lauri Juvela, Xin Wang
Automatic detection of synthetic speech is becoming increasingly important as current synthesis methods are both near indistinguishable from human speech and widely accessible to t…
HiFi-Glot: High-Fidelity Neural Formant Synthesis with Differentiable Resonant Filters
Yicheng Gu, Pablo Pérez Zarazaga, Chaoren Wang +4
Formant synthesis aims to generate speech with controllable formant structures, enabling precise control of vocal resonance and phonetic features. However, while existing formant s…
End-to-End Amp Modeling: From Data to Controllable Guitar Amplifier Models
Lauri Juvela, Eero-Pekka Damskägg, Aleksi Peussa +4
This paper describes a data-driven approach to creating real-time neural network models of guitar amplifiers, recreating the amplifiers' sonic response to arbitrary inputs at the f…
DDSP-based Neural Waveform Synthesis of Polyphonic Guitar Performance from String-wise MIDI Input
Nicolas Jonason, Xin Wang, Erica Cooper +3
We explore the use of neural synthesis for acoustic guitar from string-wise MIDI input. We propose four different systems and compare them with both objective metrics and subjectiv…
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention
Bajibabu Bollepalli, Lauri Juvela, Paavo Alku
Currently, there are increasing interests in text-to-speech (TTS) synthesis to use sequence-to-sequence models with attention. These models are end-to-end meaning that they learn b…