514 citations · 1.4k across the 79 of their papers we have counts for
9 papers · 1 filter
OSSEM: one-shot speaker adaptive speech enhancement using meta learning
Cheng Yu, Szu-Wei Fu, Tsun-An Hsieh +2
Although deep learning (DL) has achieved notable progress in speech enhancement (SE), further research is still required for a DL-based SE system to adapt effectively and efficient…
REAL-M: Towards Speech Separation on Real Mixtures
Cem Subakan, Mirco Ravanelli, Samuele Cornell +1
In recent years, deep learning based source separation has achieved impressive results. Most studies, however, still evaluate separation models on synthetic datasets, while the per…
MetricGAN-U: Unsupervised speech enhancement/ dereverberation based only on noisy/ reverberated speech
Szu-Wei Fu, Cheng Yu, Kuo-Hsuan Hung +2
Most of the deep learning-based speech enhancement models are learned in a supervised manner, which implies that pairs of noisy and clean speech are required during training. Conse…
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity
Juan Manuel Mayor-Torres, Mirco Ravanelli, Sara E. Medina-DeVilliers +2
Machine learning methods, such as deep learning, show promising results in the medical domain. However, the lack of interpretability of these algorithms may hinder their applicabil…
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…
ECAPA-TDNN Embeddings for Speaker Diarization
Nauman Dawalatabad, Mirco Ravanelli, François Grondin +3
Learning robust speaker embeddings is a crucial step in speaker diarization. Deep neural networks can accurately capture speaker discriminative characteristics and popular deep emb…
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…
Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers
Loren Lugosch, Piyush Papreja, Mirco Ravanelli +2
This paper introduces Timers and Such, a new open source dataset of spoken English commands for common voice control use cases involving numbers. We describe the gap in existing sp…
Transformers with Competitive Ensembles of Independent Mechanisms
Alex Lamb, Di He, Anirudh Goyal +4
An important development in deep learning from the earliest MLPs has been a move towards architectures with structural inductive biases which enable the model to keep distinct sour…