Results demonstrate that explicitly coupling count- and boundary-aware revision with joint reward optimization provides an effective and verifiable path to temporal audio grounding.
Yu-Hang Dai, Xin Shu, Zhen-Nan Lin 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
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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