9 citations · 13 across the 5 of their papers we have counts for
5 papers
Advancing Multi-grained Alignment for Contrastive Language-Audio Pre-training
Yiming Li, Zhifang Guo, Xiangdong Wang +1
Recent advances have been witnessed in audio-language joint learning, such as CLAP, that shows much success in multi-modal understanding tasks. These models usually aggregate uni-m…
Audio Generation with Multiple Conditional Diffusion Model
Zhifang Guo, Jianguo Mao, Rui Tao +4
Text-based audio generation models have limitations as they cannot encompass all the information in audio, leading to restricted controllability when relying solely on text. To add…
Leveraging Language Model Capabilities for Sound Event Detection
Hualei Wang, Jianguo Mao, Zhifang Guo +3
Large language models reveal deep comprehension and fluent generation in the field of multi-modality. Although significant advancements have been achieved in audio multi-modality,…
PromptTTS: Controllable Text-to-Speech with Text Descriptions
Zhifang Guo, Yichong Leng, Yihan Wu +2
Using a text description as prompt to guide the generation of text or images (e.g., GPT-3 or DALLE-2) has drawn wide attention recently. Beyond text and image generation, in this w…
A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4
Yiming Li, Zhifang Guo, Zhirong Ye +6
In this paper, we describe in detail our system for DCASE 2022 Task4. The system combines two considerably different models: an end-to-end Sound Event Detection Transformer (SEDT)…