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
Human speech includes nonverbal vocalizations (NVVs), such as laughter, sighs, breaths, and coughs, which convey affective and interactional information. Existing approaches typically represent NVVs as transcript-level tags, providing limited supervision for their waveform-time boundaries. We present NVV-Locator for fi...
Yuang Cao, Bing-Shen Mu, Zhen-Nan Lin et al.· 1 citation
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
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
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
Symbolic models make melody, harmony, rhythm, and form explicit but typically stop before a finished recording; audio models produce complete songs while leaving composition implicit. We introduce YuE2, which unifies symbolic and audio music generation at frontier quality through symbolic planning. A single AR-NAR Mixt...
Rui-Bin Yuan, Jia-Hao Pan, Jun-Yan Jiang et al.· 1 citation
Non-verbal vocalizations (NVVs) carry important paralinguistic information but are often omitted by conventional automatic speech recognition (ASR) systems. The ISCSLP NVVSpeech Challenge requires joint transcription of lexical content and 16 NVV categories under limited and highly imbalanced supervision. We present a...
Shang-Yue Jia, Jing-Ru Ma, Yang-Ze Li et al.· 1 citation
Recently, text-to-speech systems have made significant progress in speech expressiveness and controllability. However, the speaking style of generated speech typically relies on clear user-specified instructions. In natural conversations, speaking style should be naturally inferred from the preceding conversational con...
Wei-Zhen Bian, Si-Tong Cheng, Rongxiu Zhong et al.· 0 citations
This paper summarizes the ChinaVoices Challenge 2026, which aims to establish unified task definitions and evaluation conditions for Chinese dialect speech processing and to advance multi-dialect identification and automatic speech recognition. The challenge covers 16 dialect categories and defines two tasks: Chinese M...
Yu-Jie Liao, Bing-Shen Mu, Shui-Yuan Wang et al.· 0 citations
A Context-Aware Direct Preference Optimization (CA-DPO) method that significantly outperforms the baseline across all objective and subjective metrics, and establishes an evaluation method featuring a 500-sample test set and an LLM-as-Judge framework to independently assess reasoning and execution fidelity.
Jing-Bin Hu, Lu-Yu Wang, Wen-Jie Tian et al.· 0 citations
Recent advances in large language models (LLMs) and multimodal LLMs (MLLMs) have created new opportunities for wearable speech interfaces, with smart glasses providing an egocentric platform for continuous audio sensing and assistance. However, speech recognition and understanding in this setting remain challenging bec...
Dehui Gao, Zhixian Zhao, Zhennan Lin et al.· 1 citation
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