5 citations · 6 across the 5 of their papers we have counts for
7 papers
Unsupervised Speech Enhancement using Data-defined Priors
Dominik Klement, Matthew Maciejewski, Sanjeev Khudanpur +2
The majority of deep learning-based speech enhancement methods require paired clean-noisy speech data. Collecting such data at scale in real-world conditions is infeasible, which h…
The CHiME-8 DASR Challenge for Generalizable and Array Agnostic Distant Automatic Speech Recognition and Diarization
Samuele Cornell, Taejin Park, Steve Huang +6
This paper presents the CHiME-8 DASR challenge which carries on from the previous edition CHiME-7 DASR (C7DASR) and the past CHiME-6 challenge. It focuses on joint multi-channel di…
On Speaker Attribution with SURT
Desh Raj, Matthew Wiesner, Matthew Maciejewski +3
The Streaming Unmixing and Recognition Transducer (SURT) has recently become a popular framework for continuous, streaming, multi-talker speech recognition (ASR). With advances in…
Training Noisy Single-Channel Speech Separation With Noisy Oracle Sources: A Large Gap and A Small Step
Matthew Maciejewski, Jing Shi, Shinji Watanabe +1
As the performance of single-channel speech separation systems has improved, there has been a desire to move to more challenging conditions than the clean, near-field speech that i…
The JHU Multi-Microphone Multi-Speaker ASR System for the CHiME-6 Challenge
Ashish Arora, Desh Raj, Aswin Shanmugam Subramanian +7
This paper summarizes the JHU team's efforts in tracks 1 and 2 of the CHiME-6 challenge for distant multi-microphone conversational speech diarization and recognition in everyday h…
WHAMR!: Noisy and Reverberant Single-Channel Speech Separation
Matthew Maciejewski, Gordon Wichern, Emmett McQuinn +1
While significant advances have been made with respect to the separation of overlapping speech signals, studies have been largely constrained to mixtures of clean, near anechoic sp…