10 papers
Semantic Refinement of Universal Audio Representations through Audio-Description Alignment
Lejun Min, Junyu Dai, Ruichen Zheng +7
Universal audio representations must preserve acoustic detail while making high-level concepts accessible across speech, music, environmental sound, and downstream models of differ…
Is Semantics Enough for Speech Mean Opinion Score Prediction?
Tianyu Lan, Yufei Shi, Yang Ai +3
Mean Opinion Score (MOS) is the gold standard for evaluating synthesized speech naturalness. However, current automatic MOS predictors are dominated by self-supervised learning (SS…
Beyond Reconstruction: Full-Context Generative DiT for Music Generation
Yunjia Li, Menglin Wu, Junyu Dai +13
Hybrid music generators combine the long-range planning of an autoregressive language model with the fidelity of a diffusion- or flow-based acoustic renderer. Yet renderers are tra…
Qwen-Audio-3.0-Gen-Preview Technical Report
Junyu Dai, Xiaoyue Duan, Xinyue Fan +14
Existing single-domain and multi-task audio systems remain limited in directly organizing heterogeneous audio components, ambience, and multiple roles into long-form temporal scene…
Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering
Junyu Dai, Xinyue Fan, Weiqin Li +14
In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and musical attributes. The propo…
UniVocal: Unified Speech-Singing Code-Switching Synthesis
Yufei Shi, Qian Chen, Wen Wang +3
We propose UniVocal, a unified framework that implicitly infers vocal modes from text context to pioneer Speech-Singing Code-Switching (SCS) Synthesis - a task where transitions ar…
LatentFlowSR: High-Fidelity Audio Super-Resolution via Noise-Robust Latent Flow Matching
Fei Liu, Yang Ai, Hui-Peng Du +2
Audio super-resolution aims to recover missing high-frequency details from bandwidth-limited low-resolution audio, thereby improving the naturalness and perceptual quality of the r…
Universal Preference-Score-based Pairwise Speech Quality Assessment
Yu-Fei Shi, Yang Ai, Zhen-Hua Ling
To compare the performance of two speech generation systems, one of the most effective approaches is estimating the preference score between their generated speech. This paper prop…
Pitch-and-Spectrum-Aware Singing Quality Assessment with Bias Correction and Model Fusion
Yu-Fei Shi, Yang Ai, Ye-Xin Lu +2
We participated in track 2 of the VoiceMOS Challenge 2024, which aimed to predict the mean opinion score (MOS) of singing samples. Our submission secured the first place among all…
SAMOS: A Neural MOS Prediction Model Leveraging Semantic Representations and Acoustic Features
Yu-Fei Shi, Yang Ai, Ye-Xin Lu +2
Assessing the naturalness of speech using mean opinion score (MOS) prediction models has positive implications for the automatic evaluation of speech synthesis systems. Early MOS p…