1 citations · 3 across the 15 of their papers we have counts for
17 papers
FOAdapter: A Plug-and-Play Spatial Tokenizer for Low-Bitrate FOA Speech Coding
Kirak Kim, Yoonjeong Park, Juhan Nam +2
Spatially encoded speech conveys not only linguistic information but also spatial cues. This enables listeners to distinguish and localize speakers, contributing to more natural an…
BenchmarkAnything: Agent-Driven Construction of Simulator-Ready Microarchitecture Benchmarks
Xiangfeng Sun, Ceyu Xu, Chen Bai +1
The selection of benchmark workloads is of paramount importance in computer architecture, as it establishes the yardstick against which architectural innovations are measured and g…
MeloDISinger: Melody-Aware & Duration-Preserving Singing Voice Editing with Audio Infilling
Yoonjeong Park, Jaekwon Im, Juhan Nam
Text-based singing voice editing (SVE) aims to revise sung lyrics while preserving the original melody, total duration, and non-edited regions. In this paper, we propose MeloDISing…
DTM-Codec: Dynamic Token Masking for VFR Speech Coding with Efficient Boundary Selection
Hoyeol Sohn, Juhan Nam
Variable frame rate (VFR) coding has recently emerged in neural speech codecs, allocating fewer frames to redundant regions and more frames to rapidly changing speech. VFR must tra…
SDP-Codec: A Speaker-Decoupled Speech Codec with Pitch Injection for Low-Bitrate Coding and Zero-Shot Voice Conversion
Hounsu Kim, Juhan Nam
Speaker-decoupled speech codecs can reduce bitrate by separating global speaker attributes from local content and prosody, while supporting voice conversion. Existing speaker-decou…
AdaTT: Text-Guided Instrument Timbre Transfer with Target-Adaptive Structural Control
Dabin Kim, Junwon Lee, Juhan Nam
This paper addresses timbral ambiguity in instrument timbre transfer under fine-grained structural conditions. We argue this issue stems from instrument-specific expressive details…
CounterFlow: A Two-Phase Inference-Time Sampling for Counterfactual Video Foley Generation
Gyubin Lee, Junwon Lee, Juhan Nam
We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining temporally synchronized to a…
UNMIXX: Untangling Highly Correlated Singing Voices Mixtures
Jihoo Jung, Ji-Hoon Kim, Doyeop Kwak +3
We introduce UNMIXX, a novel framework for multiple singing voices separation (MSVS). While related to speech separation, MSVS faces unique challenges: data scarcity and the highly…
Hear What Matters! Text-conditioned Selective Video-to-Audio Generation
Junwon Lee, Juhan Nam, Jiyoung Lee
This work introduces a new task, text-conditioned selective video-to-audio (V2A) generation, which produces only the user-intended sound from a multi-object video. This capability…
SAGA-SR: Semantically and Acoustically Guided Audio Super-Resolution
Jaekwon Im, Juhan Nam
Versatile audio super-resolution (SR) aims to predict high-frequency components from low-resolution audio across diverse domains such as speech, music, and sound effects. Existing…
KAD: No More FAD! An Effective and Efficient Evaluation Metric for Audio Generation
Yoonjin Chung, Pilsun Eu, Junwon Lee +3
Although being widely adopted for evaluating generated audio signals, the Fréchet Audio Distance (FAD) suffers from significant limitations, including reliance on Gaussian assumpti…
FlashSR: One-step Versatile Audio Super-resolution via Diffusion Distillation
Jaekwon Im, Juhan Nam
Versatile audio super-resolution (SR) is the challenging task of restoring high-frequency components from low-resolution audio with sampling rates between 4kHz and 32kHz in various…
Video-Foley: Two-Stage Video-To-Sound Generation via Temporal Event Condition For Foley Sound
Junwon Lee, Jaekwon Im, Dabin Kim +1
Foley sound synthesis is crucial for multimedia production, enhancing user experience by synchronizing audio and video both temporally and semantically. Recent studies on automatin…
CONMOD: Controllable Neural Frame-based Modulation Effects
Gyubin Lee, Hounsu Kim, Junwon Lee +1
Deep learning models have seen widespread use in modelling LFO-driven audio effects, such as phaser and flanger. Although existing neural architectures exhibit high-quality emulati…
Expressive Acoustic Guitar Sound Synthesis with an Instrument-Specific Input Representation and Diffusion Outpainting
Hounsu Kim, Soonbeom Choi, Juhan Nam
Synthesizing performing guitar sound is a highly challenging task due to the polyphony and high variability in expression. Recently, deep generative models have shown promising res…
T-FOLEY: A Controllable Waveform-Domain Diffusion Model for Temporal-Event-Guided Foley Sound Synthesis
Yoonjin Chung, Junwon Lee, Juhan Nam
Foley sound, audio content inserted synchronously with videos, plays a critical role in the user experience of multimedia content. Recently, there has been active research in Foley…
DIFFRENT: A Diffusion Model for Recording Environment Transfer of Speech
Jaekwon Im, Juhan Nam
Properly setting up recording conditions, including microphone type and placement, room acoustics, and ambient noise, is essential to obtaining the desired acoustic characteristics…