104 citations · 200 across the 24 of their papers we have counts for
11 papers · 1 filter
Boosting Unknown-number Speaker Separation with Transformer Decoder-based Attractor
Younglo Lee, Shukjae Choi, Byeong-Yeol Kim +2
We propose a novel speech separation model designed to separate mixtures with an unknown number of speakers. The proposed model stacks 1) a dual-path processing block that can mode…
A Single Speech Enhancement Model Unifying Dereverberation, Denoising, Speaker Counting, Separation, and Extraction
Kohei Saijo, Wangyou Zhang, Zhong-Qiu Wang +3
We propose a multi-task universal speech enhancement (MUSE) model that can perform five speech enhancement (SE) tasks: dereverberation, denoising, speech separation (SS), target sp…
The Multimodal Information Based Speech Processing (MISP) 2023 Challenge: Audio-Visual Target Speaker Extraction
Shilong Wu, Chenxi Wang, Hang Chen +13
Previous Multimodal Information based Speech Processing (MISP) challenges mainly focused on audio-visual speech recognition (AVSR) with commendable success. However, the most advan…
Toward Universal Speech Enhancement for Diverse Input Conditions
Wangyou Zhang, Kohei Saijo, Zhong-Qiu Wang +2
The past decade has witnessed substantial growth of data-driven speech enhancement (SE) techniques thanks to deep learning. While existing approaches have shown impressive performa…
The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
Samuele Cornell, Matthew Wiesner, Shinji Watanabe +8
The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems. We introduce the CHiME-7 distant ASR (DA…
Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks
Darius Petermann, Gordon Wichern, Aswin Shanmugam Subramanian +2
Emulating the human ability to solve the cocktail party problem, i.e., focus on a source of interest in a complex acoustic scene, is a long standing goal of audio source separation…
ESPnet-SE++: Speech Enhancement for Robust Speech Recognition, Translation, and Understanding
Yen-Ju Lu, Xuankai Chang, Chenda Li +10
This paper presents recent progress on integrating speech separation and enhancement (SSE) into the ESPnet toolkit. Compared with the previous ESPnet-SE work, numerous features hav…
Locate This, Not That: Class-Conditioned Sound Event DOA Estimation
Olga Slizovskaia, Gordon Wichern, Zhong-Qiu Wang +1
Existing systems for sound event localization and detection (SELD) typically operate by estimating a source location for all classes at every time instant. In this paper, we propos…
Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
Yen-Ju Lu, Samuele Cornell, Xuankai Chang +5
This paper describes our submission to the L3DAS22 Challenge Task 1, which consists of speech enhancement with 3D Ambisonic microphones. The core of our approach combines Deep Neur…
The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks
Darius Petermann, Gordon Wichern, Zhong-Qiu Wang +1
The cocktail party problem aims at isolating any source of interest within a complex acoustic scene, and has long inspired audio source separation research. Recent efforts have mai…
Multi-Microphone Complex Spectral Mapping for Speech Dereverberation
Zhong-Qiu Wang, DeLiang Wang
This study proposes a multi-microphone complex spectral mapping approach for speech dereverberation on a fixed array geometry. In the proposed approach, a deep neural network (DNN)…