Recent advances in speech generation are shifting toward context-aware, multi-turn, and multi-speaker synthesis. While these capabilities are in high demand for applications such as audiobook and audio drama production, evaluation has not kept pace with these advances. Beyond traditional zero-shot Text-to-Speech (TTS),...
Jing-Bin Hu, Zi-Tao Yang, Xiao-Ge Peng et al.· 0 citations
We propose a preference optimization framework with Large Audio-Language Model (LALM) feedback for controllable non-verbal vocalization (NVV) generation in continuous autoregressive speech models. To construct preference data without human preference annotation, we build a bilingual prompt corpus by combining NVV-injec...
Jing-Bin Hu, Qi-Rui Zhan, Yuang Cao et al.· 3 citations
Nonverbal vocalizations (NVVs), such as laughter, sighs, breaths, and coughs, convey affective and interactional information that conventional automatic speech recognition (ASR) systems often discard. We present a bilingual Mandarin-English system for Track 1 of the NVVSpeech Challenge at ISCSLP 2026, which requires jo...
Yuang Cao, Qi-Rui Zhan, Jing-Bin Hu et al.· 2 citations
Progress in dialectal speech technology is hindered by the scarcity of large-scale, real-world corpora. For Minnan speech, existing resources remain limited, and few provide paired Minnan and Mandarin transcripts at scale. To address these gaps, we introduce WenetSpeech-Min, an open-source corpus comprising around 10,0...
Hao-Yu Zhang, Chun-Jiang He, Hong-Tao Li et al.· 0 citations
SphereVAE is proposed, which constrains the VAE latent space to the unit hypersphere and regularizes the latent distribution toward a uniform prior, so that information is encoded mainly by directional variation, providing a bounded geometric target for autoregressive prediction and reducing the risk of norm drift.
Hao-Yu Zhang, Jing-Bin Hu, Han-Ke Xie et al.· 0 citations
An NVV-aware DiTAR system that models continuous speech latents, encodes the 16 target NVV categories as dedicated to- kens, and adapts stop prediction to distinguish mid-utterance vocalizations from utterance boundaries is developed.
Zi-Yu Zhang, Yun Chen, Tai-Hui Wang et al.· 1 citation· ⚡1
The proposed DiTAR+, a dual-optimization framework for continuous-latent Autoregressive Diffusion Transformer models, introduces Dilated Context Sampling and Hierarchical Acoustic Masking to prevent shallow layers from attending to acoustic pre-context, explicitly decoupling semantic alignment from acoustic detail reco...
Zi-Yu Zhang, Tian-Lun Zuo, Han-Zhao Li et al.· 0 citations
Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insufficiently diagnosed. Existing evaluations mainly focus on naturalness, speaker similarity, and content consistency using regular test sentences, while providing limited ins...
Tian-Lun Zuo, Zi-Yu Zhang, Tingzhi Mao et al.· 0 citations
It is shown that structured LLM prompting and scalar supervision collapse rubric dimensions, yielding near-zero correlation with human ratings and strong cross-dimension coupling, are effective for segment-level SI evaluation.
Zi-Yu Zhang, Satoshi Nakamura· 0 citations
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