19 citations · 56 across the 36 of their papers we have counts for
12 papers · 1 filter
Speech Watermarking with Discrete Intermediate Representations
Shengpeng Ji, Ziyue Jiang, Jialong Zuo +4
Speech watermarking techniques can proactively mitigate the potential harmful consequences of instant voice cloning techniques. These techniques involve the insertion of signals in…
WavChat: A Survey of Spoken Dialogue Models
Shengpeng Ji, Yifu Chen, Minghui Fang +16
Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o, have captured significant attention in the speech domain. Compared to traditional three-tier casc…
LLaVA-MR: Large Language-and-Vision Assistant for Video Moment Retrieval
Weiheng Lu, Jian Li, An Yu +3
Multimodal Large Language Models (MLLMs) are widely used for visual perception, understanding, and reasoning. However, long video processing and precise moment retrieval remain cha…
OmniSep: Unified Omni-Modality Sound Separation with Query-Mixup
Xize Cheng, Siqi Zheng, Zehan Wang +8
The scaling up has brought tremendous success in the fields of vision and language in recent years. When it comes to audio, however, researchers encounter a major challenge in scal…
MuVi: Video-to-Music Generation with Semantic Alignment and Rhythmic Synchronization
Ruiqi Li, Siqi Zheng, Xize Cheng +3
Generating music that aligns with the visual content of a video has been a challenging task, as it requires a deep understanding of visual semantics and involves generating music w…
WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling
Shengpeng Ji, Ziyue Jiang, Wen Wang +14
Language models have been effectively applied to modeling natural signals, such as images, video, speech, and audio. A crucial component of these models is the codec tokenizer, whi…
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs
Keyu An, Qian Chen, Chong Deng +30
This report introduces FunAudioLLM, a model family designed to enhance natural voice interactions between humans and large language models (LLMs). At its core are two innovative mo…
CART: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling
Minghui Fang, Shengpeng Ji, Jialong Zuo +9
Cross-modal retrieval aims to search for instances, which are semantically related to the query through the interaction of different modal data. Traditional solutions utilize a sin…
ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control
Shengpeng Ji, Qian Chen, Wen Wang +8
In this paper, we present ControlSpeech, a text-to-speech (TTS) system capable of fully cloning the speaker's voice and enabling arbitrary control and adjustment of speaking style.…
Enhancing Multimodal Unified Representations for Cross Modal Generalization
Hai Huang, Yan Xia, Shengpeng Ji +7
To enhance the interpretability of multimodal unified representations, many studies have focused on discrete unified representations. These efforts typically start with contrastive…
Language-Codec: Bridging Discrete Codec Representations and Speech Language Models
Shengpeng Ji, Minghui Fang, Jialong Zuo +5
In recent years, large language models have achieved significant success in generative tasks related to speech, audio, music, and other signal domains. A crucial element of these m…
MobileSpeech: A Fast and High-Fidelity Framework for Mobile Zero-Shot Text-to-Speech
Shengpeng Ji, Ziyue Jiang, Hanting Wang +2
Zero-shot text-to-speech (TTS) has gained significant attention due to its powerful voice cloning capabilities, requiring only a few seconds of unseen speaker voice prompts. Howeve…