activity
20222026
most citedAn Initial Investigation for Detecting Vocoder Fingerprints of Fake Audio

28 citations · 57 across the 30 of their papers we have counts for

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Showing 2024Show all

11 papers · 1 filter

cs.SD2024

Mel-Refine: A Plug-and-Play Approach to Refine Mel-Spectrogram in Audio Generation

Hongming Guo, Ruibo Fu, Yizhong Geng +9

Text-to-audio (TTA) model is capable of generating diverse audio from textual prompts. However, most mainstream TTA models, which predominantly rely on Mel-spectrograms, still face…

cs.SD2024

DPI-TTS: Directional Patch Interaction for Fast-Converging and Style Temporal Modeling in Text-to-Speech

Xin Qi, Ruibo Fu, Zhengqi Wen +12

In recent years, speech diffusion models have advanced rapidly. Alongside the widely used U-Net architecture, transformer-based models such as the Diffusion Transformer (DiT) have…

eess.AS2024

Text Prompt is Not Enough: Sound Event Enhanced Prompt Adapter for Target Style Audio Generation

Chenxu Xiong, Ruibo Fu, Shuchen Shi +9

Current mainstream audio generation methods primarily rely on simple text prompts, often failing to capture the nuanced details necessary for multi-style audio generation. To addre…

cs.SD2024

WMCodec: End-to-End Neural Speech Codec with Deep Watermarking for Authenticity Verification

Junzuo Zhou, Jiangyan Yi, Yong Ren +3

Recent advances in speech spoofing necessitate stronger verification mechanisms in neural speech codecs to ensure authenticity. Current methods embed numerical watermarks before co…

eess.AS2024

VQ-CTAP: Cross-Modal Fine-Grained Sequence Representation Learning for Speech Processing

Chunyu Qiang, Wang Geng, Yi Zhao +12

Deep learning has brought significant improvements to the field of cross-modal representation learning. For tasks such as text-to-speech (TTS), voice conversion (VC), and automatic…

eess.AS2024

ICAGC 2024: Inspirational and Convincing Audio Generation Challenge 2024

Ruibo Fu, Rui Liu, Chunyu Qiang +11

The Inspirational and Convincing Audio Generation Challenge 2024 (ICAGC 2024) is part of the ISCSLP 2024 Competitions and Challenges track. While current text-to-speech (TTS) techn…

eess.AS2024

ASRRL-TTS: Agile Speaker Representation Reinforcement Learning for Text-to-Speech Speaker Adaptation

Ruibo Fu, Xin Qi, Zhengqi Wen +10

Speaker adaptation, which involves cloning voices from unseen speakers in the Text-to-Speech task, has garnered significant interest due to its numerous applications in multi-media…

eess.AS2024

MINT: a Multi-modal Image and Narrative Text Dubbing Dataset for Foley Audio Content Planning and Generation

Ruibo Fu, Shuchen Shi, Hongming Guo +12

Foley audio, critical for enhancing the immersive experience in multimedia content, faces significant challenges in the AI-generated content (AIGC) landscape. Despite advancements…

cs.SD2024

PPPR: Portable Plug-in Prompt Refiner for Text to Audio Generation

Shuchen Shi, Ruibo Fu, Zhengqi Wen +10

Text-to-Audio (TTA) aims to generate audio that corresponds to the given text description, playing a crucial role in media production. The text descriptions in TTA datasets lack ri…

cs.SD2024

TraceableSpeech: Towards Proactively Traceable Text-to-Speech with Watermarking

Junzuo Zhou, Jiangyan Yi, Tao Wang +5

Various threats posed by the progress in text-to-speech (TTS) have prompted the need to reliably trace synthesized speech. However, contemporary approaches to this task involve add…

cs.CV2024★ 1 cited

Anything in Any Scene: Photorealistic Video Object Insertion

Chen Bai, Zeman Shao, Guoxiang Zhang +11

Realistic video simulation has shown significant potential across diverse applications, from virtual reality to film production. This is particularly true for scenarios where captu…