6 papers
Bagpiper-Edit: Zero-Shot Open-Ended Audio Editing via Rich-Caption
Xun Gong, Jinchuan Tian, Haoran Wang +3
Current text-guided audio editing methods rely on paired training data, predefined operation templates, and separate processing pipelines across speech, music, and sound. We presen…
JASTIN: Aligning LLMs for Zero-Shot Audio and Speech Evaluation via Natural Language Instructions
Leying Zhang, Bowen Shi, Haibin Wu +2
The rapid advancement of generative audio models has outpaced the development of robust evaluation methodologies. Existing objective metrics and general multimodal large language m…
DeepASMR: LLM-Based Zero-Shot ASMR Speech Generation for Anyone of Any Voice
Leying Zhang, Tingxiao Zhou, Haiyang Sun +2
While modern Text-to-Speech (TTS) systems achieve high fidelity for read-style speech, they struggle to generate Autonomous Sensory Meridian Response (ASMR), a specialized, low-int…
Training Text-to-Speech Model with Purely Synthetic Data: Feasibility, Sensitivity, and Generalization Capability
Tingxiao Zhou, Leying Zhang, Zhengyang Chen +1
The potential of synthetic data in text-to-speech (TTS) model training has gained increasing attention, yet its rationality and effectiveness require systematic validation. In this…
Advanced Zero-Shot Text-to-Speech for Background Removal and Preservation with Controllable Masked Speech Prediction
Leying Zhang, Wangyou Zhang, Zhengyang Chen +1
The acoustic background plays a crucial role in natural conversation. It provides context and helps listeners understand the environment, but a strong background makes it difficult…
SLIDE: Integrating Speech Language Model with LLM for Spontaneous Spoken Dialogue Generation
Haitian Lu, Gaofeng Cheng, Liuping Luo +3
Recently, ``textless" speech language models (SLMs) based on speech units have made huge progress in generating naturalistic speech, including non-verbal vocalizations. However, th…