Nonverbal vocalizations (NVVs), such as laughter and sighs, convey meaning alongside words. NVV-aware speech systems must recognize and generate these events while preserving lexical accuracy and perceptual quality. Yet differences in annotation, resources, and evaluation complicate comparisons, and aggregate scores ca...
Liu-Meng Xue, Yuang Cao, Jing-Bin Hu et al.· 0 citations
Continuous latent representations underlie recent diffusion-based lyrics-to-song and text-to-music systems, yet aligning lyric conditions with these latents remains difficult: existing systems resort to generator-side machinery such as sentence-level timestamps, auxiliary alignment objectives, or semi-autoregressive de...
Guo-Bin Ma, Yue-Peng Jiang, Da-Ke Guo 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
Recent controllable speech generation requires training data with fine-grained annotations of speaker traits, prosody, emotion, paralinguistic cues, acoustic scenes, and context. Existing workflows often rely on manual correction, paid hosted multimodal services, or fixed processing chains, which limits large-scale dat...
Qi-Rui Zhan, Shui-Yuan Wang, Jing-Bin Hu et al.· 0 citations
StreamTN is proposed, a lightweight LLM-based Chinese streaming TN model that employs a dual-track streaming framework in which input tokens and output tokens are processed on two parallel tracks, enabling low-latency real-time inference without complex prompting.
Wen-Hao Li, Jin-Rui Liang, Hao-Yu Zhang et al.· 0 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
Discrete audio tokenization has become the critical interface between raw waveforms and autoregressive modeling in recent music generation. As a result, music tokenizers must simultaneously support high-fidelity reconstruction and produce discrete sequences that remain amenable to language modeling. Existing reconstruc...
Hua-Kang Chen, Guo-Bin Ma, Yue-Peng Jiang et al.· 0 citations
Dynamic speaking style adaptation in multi-turn multimodal interaction remains a major challenge for text-to-speech (TTS) systems. Existing context-aware TTS (CTTS) methods typically map dialogue context to speech in an end-to-end manner. Such implicit modeling makes contextual style decisions difficult to supervise, w...
Wen-Jie Tian, Kang-Xiang Xia, Jing-Bin Hu 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
A controllable multi-speaker dialogue TTS framework that formulates synthesis as critique-driven iterative refinement, and unifies instruction-following synthesis and natural-language-guided attribute editing, enabling correction of expressive errors without full regeneration.
Kang-Xiang Xia, Xin-Fa Zhu, Hang-Rui Hu et al.· 0 citations
X-Pred MeanFlow is proposed, a few-step streaming token-to-mel decoder that reparameterizes MeanFlow with mel-space prediction and introduces layer-selective block-wise attention to enable continuous chunk-wise generation with bounded context.
Han-Ke Xie, Xia-Ming Ren, Qi-Rui Zhan et al.· 0 citations
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