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Results demonstrate that explicitly coupling count- and boundary-aware revision with joint reward optimization provides an effective and verifiable path to temporal audio grounding.
Recent advances in large audio language models (LALMs) have driven the development of natural and intelligent speech interaction systems. Such systems need to model complex conversational behaviors, including turn-taking, overlapping speech, and speaker coordination. Multi-party conversations provide a realistic settin...
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.
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...
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.
SemBridge is proposed, a training-only semantic-token anchoring framework for continuous-latent autoregressive speech generation and demonstrates that explicit semantic-token supervision for autoregressive state learning is an effective and general direction for continuous speech generation.
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