3 citations · 3 across the 6 of their papers we have counts for
6 papers
Breaking the Quality--Intelligibility Trade-off in Streaming Target Speaker Extraction via Deep-Feature-Anchored Preference Optimization
Shuhai Peng, Jinjiang Liu, Hui Lu +5
Generative streaming models for Target Speaker Extraction (TSE) commonly exhibit a quality--intelligibility trade-off, wherein naive optimization for perceptual audio quality tends…
StarTSE: Towards Streaming Target Speaker Extraction via Chunk-wise Interleaved Splicing of Autoregressive Language Model
Shuhai Peng, Hui Lu, Jinjiang Liu +8
While generative models have set new benchmarks for Target Speaker Extraction (TSE), their inherent reliance on global context precludes deployment in real-time applications. Direc…
InteractiveOmni: A Unified Omni-modal Model for Audio-Visual Multi-turn Dialogue
Wenwen Tong, Hewei Guo, Dongchuan Ran +23
We introduce InteractiveOmni, a unified and open-source omni-modal large language model for audio-visual multi-turn interaction, ranging from 4B to 8B parameters, designed to lead…
CIF-T: A Novel CIF-based Transducer Architecture for Automatic Speech Recognition
Tian-Hao Zhang, Dinghao Zhou, Guiping Zhong +2
RNN-T models are widely used in ASR, which rely on the RNN-T loss to achieve length alignment between input audio and target sequence. However, the implementation complexity and th…
Dynamic Latency for CTC-Based Streaming Automatic Speech Recognition With Emformer
Jingyu Sun, Guiping Zhong, Dinghao Zhou +1
An inferior performance of the streaming automatic speech recognition models versus non-streaming model is frequently seen due to the absence of future context. In order to improve…
Locality Matters: A Locality-Biased Linear Attention for Automatic Speech Recognition
Jingyu Sun, Guiping Zhong, Dinghao Zhou +2
Conformer has shown a great success in automatic speech recognition (ASR) on many public benchmarks. One of its crucial drawbacks is the quadratic time-space complexity with respec…