14 citations · 16 across the 13 of their papers we have counts for
8 papers · 1 filter
VoiceDesigner: Text-to-Voice Generation and Editing via Unified Diffusion Modeling and Data Augmentation
Jiarui Hai, Karan Thakkar, Ke Chen +5
Recent breakthroughs in generative models have made text-to-voice generation (TTV) possible, enabling the synthesis of speech directly from textual voice descriptions. However, exi…
FlexSED: Towards Open-Vocabulary Sound Event Detection
Jiarui Hai, Helin Wang, Weizhe Guo +1
Despite recent progress in large-scale sound event detection (SED) systems capable of handling hundreds of sound classes, existing multi-class classification frameworks remain fund…
SynSonic: Augmenting Sound Event Detection through Text-to-Audio Diffusion ControlNet and Effective Sample Filtering
Jiarui Hai, Mounya Elhilali
Data synthesis and augmentation are essential for Sound Event Detection (SED) due to the scarcity of temporally labeled data. While augmentation methods like SpecAugment and Mix-up…
EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer
Jiarui Hai, Yong Xu, Hao Zhang +4
We introduce EzAudio, a text-to-audio (T2A) generation framework designed to produce high-quality, natural-sounding sound effects. Core designs include: (1) We propose EzAudio-DiT,…
SoloAudio: Target Sound Extraction with Language-oriented Audio Diffusion Transformer
Helin Wang, Jiarui Hai, Yen-Ju Lu +3
In this paper, we introduce SoloAudio, a novel diffusion-based generative model for target sound extraction (TSE). Our approach trains latent diffusion models on audio, replacing t…
DreamVoice: Text-Guided Voice Conversion
Jiarui Hai, Karan Thakkar, Helin Wang +2
Generative voice technologies are rapidly evolving, offering opportunities for more personalized and inclusive experiences. Traditional one-shot voice conversion (VC) requires a ta…
DPM-TSE: A Diffusion Probabilistic Model for Target Sound Extraction
Jiarui Hai, Helin Wang, Dongchao Yang +3
Common target sound extraction (TSE) approaches primarily relied on discriminative approaches in order to separate the target sound while minimizing interference from the unwanted…
Joint Acoustic and Class Inference for Weakly Supervised Sound Event Detection
Sandeep Kothinti, Keisuke Imoto, Debmalya Chakrabarty +3
Sound event detection is a challenging task, especially for scenes with multiple simultaneous events. While event classification methods tend to be fairly accurate, event localizat…