514 citations · 514 across the 3 of their papers we have counts for
6 papers
SpeechBrain: A General-Purpose Speech Toolkit
Mirco Ravanelli, Titouan Parcollet, Peter Plantinga +18
SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to facilitate the research and development of neural speech processing technologies by being simple, fle…
MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement
Szu-Wei Fu, Cheng Yu, Tsun-An Hsieh +4
The discrepancy between the cost function used for training a speech enhancement model and human auditory perception usually makes the quality of enhanced speech unsatisfactory. Ob…
Phonetic Feedback for Speech Enhancement With and Without Parallel Speech Data
Peter Plantinga, Deblin Bagchi, Eric Fosler-Lussier
While deep learning systems have gained significant ground in speech enhancement research, these systems have yet to make use of the full potential of deep learning systems to prov…
Towards Real-time Mispronunciation Detection in Kids' Speech
Peter Plantinga, Eric Fosler-Lussier
Modern mispronunciation detection and diagnosis systems have seen significant gains in accuracy due to the introduction of deep learning. However, these systems have not been evalu…
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-…