3 citations · 5 across the 12 of their papers we have counts for
13 papers
Time-Bin Properties of Photon Pairs from a 2GHz Waveguide Resonator
Stefan Kazmaier, Kaisa Laiho
We produce degenerate photon pairs called signal and idler via parametric down-conversion (PDC) in a Fabry-Pérot waveguide resonator having close to a 2GHz bandwidth in the telecom…
Scalable Neural Vocoder from Range-Null Space Decomposition
Andong Li, Tong Lei, Zhihang Sun +4
Although deep neural networks have facilitated significant progress of neural vocoders in recent years, they usually suffer from intrinsic challenges like opaque modeling, inflexib…
BridgeVoC: Revitalizing Neural Vocoder from a Restoration Perspective
Andong Li, Tong Lei, Rilin Chen +5
This paper revisits the neural vocoder task through the lens of audio restoration and propose a novel diffusion vocoder called BridgeVoC. Specifically, by rank analysis, we compare…
Target matching based generative model for speech enhancement
Taihui Wang, Rilin Chen, Tong Lei +4
The design of mean and variance schedules for the perturbed signal is a fundamental challenge in generative models. While score-based and Schrödinger bridge-based models require ca…
Audio-Thinker: Guiding Audio Language Model When and How to Think via Reinforcement Learning
Shu Wu, Chenxing Li, Wenfu Wang +4
Recent advancements in large language models, multimodal large language models, and large audio language models (LALMs) have significantly improved their reasoning capabilities thr…
From Continuous to Discrete: Cross-Domain Collaborative General Speech Enhancement via Hierarchical Language Models
Zhaoxi Mu, Rilin Chen, Andong Li +3
This paper introduces OmniGSE, a novel general speech enhancement (GSE) framework designed to mitigate the diverse distortions that speech signals encounter in real-world scenarios…
FNSE-SBGAN: Far-field Speech Enhancement with Schrodinger Bridge and Generative Adversarial Networks
Tong Lei, Qinwen Hu, Ziyao Lin +5
The prevailing method for neural speech enhancement predominantly utilizes fully-supervised deep learning with simulated pairs of far-field noisy-reverberant speech and clean speec…
LLM-Enhanced Dialogue Management for Full-Duplex Spoken Dialogue Systems
Hao Zhang, Weiwei Li, Rilin Chen +3
Achieving full-duplex communication in spoken dialogue systems (SDS) requires real-time coordination between listening, speaking, and thinking. This paper proposes a semantic voice…
Neural Ambisonic Encoding For Multi-Speaker Scenarios Using A Circular Microphone Array
Yue Qiao, Vinay Kothapally, Meng Yu +1
Spatial audio formats like Ambisonics are playback device layout-agnostic and well-suited for applications such as teleconferencing and virtual reality. Conventional Ambisonic enco…
SMRU: Split-and-Merge Recurrent-based UNet for Acoustic Echo Cancellation and Noise Suppression
Zhihang Sun, Andong Li, Rilin Chen +4
The proliferation of deep neural networks has spawned the rapid development of acoustic echo cancellation and noise suppression, and plenty of prior arts have been proposed, which…
Deep Audio Zooming: Beamwidth-Controllable Neural Beamformer
Meng Yu, Dong Yu
Audio zooming, a signal processing technique, enables selective focusing and enhancement of sound signals from a specified region, attenuating others. While traditional beamforming…
Neural Network Augmented Kalman Filter for Robust Acoustic Howling Suppression
Yixuan Zhang, Hao Zhang, Meng Yu +1
Acoustic howling suppression (AHS) is a critical challenge in audio communication systems. In this paper, we propose a novel approach that leverages the power of neural networks (N…
Advancing Acoustic Howling Suppression through Recursive Training of Neural Networks
Hao Zhang, Yixuan Zhang, Meng Yu +1
In this paper, we introduce a novel training framework designed to comprehensively address the acoustic howling issue by examining its fundamental formation process. This framework…