8 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…
LSZone: A Lightweight Spatial Information Modeling Architecture for Real-time In-car Multi-zone Speech Separation
Jun Chen, Shichao Hu, Jiuxin Lin +8
In-car multi-zone speech separation, which captures voices from different speech zones, plays a crucial role in human-vehicle interaction. Although previous SpatialNet has achieved…
Accelerating Autoregressive Speech Synthesis Inference With Speech Speculative Decoding
Zijian Lin, Yang Zhang, Yougen Yuan +5
Modern autoregressive speech synthesis models leveraging language models have demonstrated remarkable performance. However, the sequential nature of next token prediction in these…
3S-TSE: Efficient Three-Stage Target Speaker Extraction for Real-Time and Low-Resource Applications
Shulin He, Jinjiang liu, Hao Li +3
Target speaker extraction (TSE) aims to isolate a specific voice from multiple mixed speakers relying on a registerd sample. Since voiceprint features usually vary greatly, current…
Speech Enhancement with Intelligent Neural Homomorphic Synthesis
Shulin He, Wei Rao, Jinjiang Liu +5
Most neural network speech enhancement models ignore speech production mathematical models by directly mapping Fourier transform spectrums or waveforms. In this work, we propose a…
LCSM: A Lightweight Complex Spectral Mapping Framework for Stereophonic Acoustic Echo Cancellation
Chenggang Zhang, Jinjiang Liu, Xueliang Zhang
The traditional adaptive algorithms will face the non-uniqueness problem when dealing with stereophonic acoustic echo cancellation (SAEC). In this paper, we first propose an effici…
Inplace Gated Convolutional Recurrent Neural Network For Dual-channel Speech Enhancement
Jinjiang Liu, Xueliang Zhang
For dual-channel speech enhancement, it is a promising idea to design an end-to-end model based on the traditional array signal processing guideline and the manifold space of multi…