4 papers
Towards Fine-Grained Multi-Dimensional Speech Understanding: Data Pipeline, Benchmark, and Model
Guojian Li, Zhixian Zhao, Zhennan Lin +9
While speech Large Language Models (LLMs) excel at conventional tasks like basic speech recognition, they lack fine-grained, multi-dimensional perception. This deficiency is eviden…
MINT-Bench: A Comprehensive Multilingual Benchmark for Instruction-Following Text-to-Speech
Huakang Chen, Jingbin Hu, Liumeng Xue +12
Instruction-following text-to-speech (TTS) has emerged as an important capability for controllable and expressive speech generation, yet its evaluation remains underdeveloped due t…
OmniCodec: Low Frame Rate Universal Audio Codec with Semantic-Acoustic Disentanglement
Jingbin Hu, Haoyu Zhang, Dake Guo +10
Large Language Models (LLMs) have advanced audio generation through discrete representation learning. However, most existing neural codecs focus on speech and emphasize reconstruct…
VoiceSculptor: Your Voice, Designed By You
Jingbin Hu, Huakang Chen, Linhan Ma +19
Despite rapid progress in text-to-speech (TTS), open-source systems still lack truly instruction-following, fine-grained control over core speech attributes (e.g., pitch, speaking…