36 citations · 98 across the 23 of their papers we have counts for
4 papers · 1 filter
Improving Neural Diarization through Speaker Attribute Attractors and Local Dependency Modeling
David Palzer, Matthew Maciejewski, Eric Fosler-Lussier
In recent years, end-to-end approaches have made notable progress in addressing the challenge of speaker diarization, which involves segmenting and identifying speakers in multi-ta…
Perceptual Loss with Recognition Model for Single-Channel Enhancement and Robust ASR
Peter Plantinga, Deblin Bagchi, Eric Fosler-Lussier
Single-channel speech enhancement approaches do not always improve automatic recognition rates in the presence of noise, because they can introduce distortions unhelpful for recogn…
An Exploration of Mimic Architectures for Residual Network Based Spectral Mapping
Peter Plantinga, Deblin Bagchi, Eric Fosler-Lussier
Spectral mapping uses a deep neural network (DNN) to map directly from noisy speech to clean speech. Our previous study found that the performance of spectral mapping improves grea…
Spectral feature mapping with mimic loss for robust speech recognition
Deblin Bagchi, Peter Plantinga, Adam Stiff +1
For the task of speech enhancement, local learning objectives are agnostic to phonetic structures helpful for speech recognition. We propose to add a global criterion to ensure de-…