6 accepted papers
Despite the significant progress of Multi-modal Large Language Models (MLLMs) across diverse tasks, hallucination, which corresponds to the generation of visually inconsistent objects, attributes, or relations, remains a major obstacle to their reliable deployment. Unlike pure language models, MLLMs
Despite the notable advances in graph-based deep multi-view clustering, existing approaches still suffer from three critical limitations: (1) relying on static graph structures and being unable to model the global semantic relationships across views; (2) contamination from false negative samples in…
Style transfer for out-of-domain (OOD) singing voice synthesis (SVS) focuses on generating high-quality singing voices with unseen styles (such as timbre, emotion, pronunciation, and articulation skills) derived from reference singing voice samples. However, the endeavor to model the intricate nuanc…
Recently, there has been a growing interest in the field of controllable Text-to-Speech (TTS). While previous studies have relied on users providing specific style factor values based on acoustic knowledge or selecting reference speeches that meet certain requirements, generating speech solely from…
Video-to-sound generation aims to generate realistic and natural sound given a video input. However, previous video-to-sound generation methods can only generate a random or average timbre without any controls of the generated sound timbre, leading to the problem that people cannot obtain the desire…
Singing voice synthesis (SVS) systems are built to synthesize high-quality and expressive singing voice, in which the acoustic model generates the acoustic features (e.g., mel-spectrogram) given a music score. Previous singing acoustic models adopt a simple loss (e.g., L1 and L2) or generative adver…