2.1k citations · 3.2k across the 30 of their papers we have counts for
30 papers
Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression
Hangting Chen, Jianwei Yu, Yi Luo +4
Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning mode…
The Sound Demixing Challenge 2023 $\unicode{x2013}$ Music Demixing Track
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai +24
This paper summarizes the music demixing (MDX) track of the Sound Demixing Challenge (SDX'23). We provide a summary of the challenge setup and introduce the task of robust music so…
Fast Random Approximation of Multi-channel Room Impulse Response
Yi Luo, Rongzhi Gu
Modern neural-network-based speech processing systems are typically required to be robust against reverberation, and the training of such systems thus needs a large amount of rever…
High Fidelity Speech Enhancement with Band-split RNN
Jianwei Yu, Yi Luo, Hangting Chen +2
Despite the rapid progress in speech enhancement (SE) research, enhancing the quality of desired speech in environments with strong noise and interfering speakers remains challengi…
Music Source Separation with Band-split RNN
Yi Luo, Jianwei Yu
The performance of music source separation (MSS) models has been greatly improved in recent years thanks to the development of novel neural network architectures and training pipel…
Improving Choral Music Separation through Expressive Synthesized Data from Sampled Instruments
Ke Chen, Hao-Wen Dong, Yi Luo +4
Choral music separation refers to the task of extracting tracks of voice parts (e.g., soprano, alto, tenor, and bass) from mixed audio. The lack of datasets has impeded research on…
FRA-RIR: Fast Random Approximation of the Image-source Method
Yi Luo, Jianwei Yu
The training of modern speech processing systems often requires a large amount of simulated room impulse response (RIR) data in order to allow the systems to generalize well in rea…
On the Use of Deep Mask Estimation Module for Neural Source Separation Systems
Kai Li, Xiaolin Hu, Yi Luo
Most of the recent neural source separation systems rely on a masking-based pipeline where a set of multiplicative masks are estimated from and applied to a signal representation o…
On the Design and Training Strategies for RNN-based Online Neural Speech Separation Systems
Kai Li, Yi Luo
While the performance of offline neural speech separation systems has been greatly advanced by the recent development of novel neural network architectures, there is typically an i…
A Time-domain Real-valued Generalized Wiener Filter for Multi-channel Neural Separation Systems
Yi Luo
Frequency-domain beamformers have been successful in a wide range of multi-channel neural separation systems in the past years. However, the operations in conventional frequency-do…
Dual-Path Modeling for Long Recording Speech Separation in Meetings
Chenda Li, Zhuo Chen, Yi Luo +6
The continuous speech separation (CSS) is a task to separate the speech sources from a long, partially overlapped recording, which involves a varying number of speakers. A straight…
Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording
Cong Han, Yi Luo, Chenda Li +8
Leveraging additional speaker information to facilitate speech separation has received increasing attention in recent years. Recent research includes extracting target speech by us…
Group Communication with Context Codec for Lightweight Source Separation
Yi Luo, Cong Han, Nima Mesgarani
Despite the recent progress on neural network architectures for speech separation, the balance between the model size, model complexity and model performance is still an important…
Ultra-Lightweight Speech Separation via Group Communication
Yi Luo, Cong Han, Nima Mesgarani
Model size and complexity remain the biggest challenges in the deployment of speech enhancement and separation systems on low-resource devices such as earphones and hearing aids. A…
Implicit Filter-and-sum Network for Multi-channel Speech Separation
Yi Luo, Nima Mesgarani
Various neural network architectures have been proposed in recent years for the task of multi-channel speech separation. Among them, the filter-and-sum network (FaSNet) performs en…
Rethinking the Separation Layers in Speech Separation Networks
Yi Luo, Zhuo Chen, Cong Han +3
Modules in all existing speech separation networks can be categorized into single-input-multi-output (SIMO) modules and single-input-single-output (SISO) modules. SIMO modules gene…
Distortion-controlled Training for End-to-end Reverberant Speech Separation with Auxiliary Autoencoding Loss
Yi Luo, Cong Han, Nima Mesgarani
The performance of speech enhancement and separation systems in anechoic environments has been significantly advanced with the recent progress in end-to-end neural network architec…
Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis
Desh Raj, Pavel Denisov, Zhuo Chen +11
Multi-speaker speech recognition of unsegmented recordings has diverse applications such as meeting transcription and automatic subtitle generation. With technical advances in syst…
An End-to-end Architecture of Online Multi-channel Speech Separation
Jian Wu, Zhuo Chen, Jinyu Li +5
Multi-speaker speech recognition has been one of the keychallenges in conversation transcription as it breaks the singleactive speaker assumption employed by most state-of-the-arts…
Separating Varying Numbers of Sources with Auxiliary Autoencoding Loss
Yi Luo, Nima Mesgarani
Many recent source separation systems are designed to separate a fixed number of sources out of a mixture. In the cases where the source activation patterns are unknown, such syste…
Real-time binaural speech separation with preserved spatial cues
Cong Han, Yi Luo, Nima Mesgarani
Deep learning speech separation algorithms have achieved great success in improving the quality and intelligibility of separated speech from mixed audio. Most previous methods focu…
Continuous speech separation: dataset and analysis
Zhuo Chen, Takuya Yoshioka, Liang Lu +6
This paper describes a dataset and protocols for evaluating continuous speech separation algorithms. Most prior studies on speech separation use pre-segmented signals of artificial…
End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation
Yi Luo, Zhuo Chen, Nima Mesgarani +1
An important problem in ad-hoc microphone speech separation is how to guarantee the robustness of a system with respect to the locations and numbers of microphones. The former requ…
Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation
Yi Luo, Zhuo Chen, Takuya Yoshioka
Recent studies in deep learning-based speech separation have proven the superiority of time-domain approaches to conventional time-frequency-based methods. Unlike the time-frequenc…