255 citations · 1.2k across the 38 of their papers we have counts for
9 papers · 1 filter
CycleGAN-Based Unpaired Speech Dereverberation
Hannah Muckenhirn, Aleksandr Safin, Hakan Erdogan +4
Typically, neural network-based speech dereverberation models are trained on paired data, composed of a dry utterance and its corresponding reverberant utterance. The main limitati…
Improving Bird Classification with Unsupervised Sound Separation
Tom Denton, Scott Wisdom, John R. Hershey
This paper addresses the problem of species classification in bird song recordings. The massive amount of available field recordings of birds presents an opportunity to use machine…
DF-Conformer: Integrated architecture of Conv-TasNet and Conformer using linear complexity self-attention for speech enhancement
Yuma Koizumi, Shigeki Karita, Scott Wisdom +4
Single-channel speech enhancement (SE) is an important task in speech processing. A widely used framework combines an analysis/synthesis filterbank with a mask prediction network,…
Sparse, Efficient, and Semantic Mixture Invariant Training: Taming In-the-Wild Unsupervised Sound Separation
Scott Wisdom, Aren Jansen, Ron J. Weiss +2
Supervised neural network training has led to significant progress on single-channel sound separation. This approach relies on ground truth isolated sources, which precludes scalin…
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…
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…
Unsupervised Sound Separation Using Mixture Invariant Training
Scott Wisdom, Efthymios Tzinis, Hakan Erdogan +3
In recent years, rapid progress has been made on the problem of single-channel sound separation using supervised training of deep neural networks. In such supervised approaches, a…
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
Quan Wang, Hannah Muckenhirn, Kevin Wilson +7
In this paper, we present a novel system that separates the voice of a target speaker from multi-speaker signals, by making use of a reference signal from the target speaker. We ac…
Deep Long Short-Term Memory Adaptive Beamforming Networks For Multichannel Robust Speech Recognition
Zhong Meng, Shinji Watanabe, John R. Hershey +1
Far-field speech recognition in noisy and reverberant conditions remains a challenging problem despite recent deep learning breakthroughs. This problem is commonly addressed by acq…