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08/28/2023
Speech Self-Supervised Representations Benchmarking: a Case for Larger Probing Heads
Self-supervised learning (SSL) leverages large datasets of unlabeled spe...
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06/30/2023
Generalization Limits of Graph Neural Networks in Identity Effects Learning
Graph Neural Networks (GNNs) have emerged as a powerful tool for data-dr...
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06/22/2023
Speech Emotion Diarization: Which Emotion Appears When?
Speech Emotion Recognition (SER) typically relies on utterance-level sol...
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06/06/2023
RescueSpeech: A German Corpus for Speech Recognition in Search and Rescue Domain
Despite recent advancements in speech recognition, there are still diffi...
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06/01/2023
Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?
Self-supervised learning (SSL) has recently allowed leveraging large dat...
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04/10/2023
Simulated Annealing in Early Layers Leads to Better Generalization
Recently, a number of iterative learning methods have been introduced to...
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03/22/2023
Posthoc Interpretation via Quantization
In this paper, we introduce a new approach, called "Posthoc Interpretati...
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03/12/2023
Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative Study
Self-supervised learning (SSL) has allowed substantial progress in Autom...
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07/27/2022
SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation
End-to-end speech synthesis models directly convert the input characters...
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06/19/2022
Resource-Efficient Separation Transformer
Transformers have recently achieved state-of-the-art performance in spee...
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05/15/2022
Learning Representations for New Sound Classes With Continual Self-Supervised Learning
In this paper, we present a self-supervised learning framework for conti...
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02/06/2022
On Using Transformers for Speech-Separation
Transformers have enabled major improvements in deep learning. They ofte...
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11/10/2021
OSSEM: one-shot speaker adaptive speech enhancement using meta learning
Although deep learning (DL) has achieved notable progress in speech enha...
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10/20/2021
REAL-M: Towards Speech Separation on Real Mixtures
In recent years, deep learning based source separation has achieved impr...
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10/12/2021
MetricGAN-U: Unsupervised speech enhancement/ dereverberation based only on noisy/ reverberated speech
Most of the deep learning-based speech enhancement models are learned in...
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07/18/2021
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity
Machine learning methods, such as deep learning, show promising results ...
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06/08/2021
SpeechBrain: A General-Purpose Speech Toolkit
SpeechBrain is an open-source and all-in-one speech toolkit. It is desig...
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04/08/2021
MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement
The discrepancy between the cost function used for training a speech enh...
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04/04/2021
Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers
This paper introduces Timers and Such, a new open source dataset of spok...
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02/27/2021
Transformers with Competitive Ensembles of Independent Mechanisms
An important development in deep learning from the earliest MLPs has bee...
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10/25/2020
Attention is All You Need in Speech Separation
Recurrent Neural Networks (RNNs) have long been the dominant architectur...
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10/19/2020
BIRD: Big Impulse Response Dataset
This paper introduces BIRD, the Big Impulse Response Dataset. This open ...
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05/18/2020
Quaternion Neural Networks for Multi-channel Distant Speech Recognition
Despite the significant progress in automatic speech recognition (ASR), ...
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01/25/2020
Multi-task self-supervised learning for Robust Speech Recognition
Despite the growing interest in unsupervised learning, extracting meanin...
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04/07/2019
Speech Model Pre-training for End-to-End Spoken Language Understanding
Whereas conventional spoken language understanding (SLU) systems map spe...
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04/06/2019
Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks
Learning good representations without supervision is still an open issue...
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12/13/2018
Speech and Speaker Recognition from Raw Waveform with SincNet
Deep neural networks can learn complex and abstract representations, tha...
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12/01/2018
Learning Speaker Representations with Mutual Information
Learning good representations is of crucial importance in deep learning....
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11/23/2018
Interpretable Convolutional Filters with SincNet
Deep learning is currently playing a crucial role toward higher levels o...
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11/21/2018
Speech recognition with quaternion neural networks
Neural network architectures are at the core of powerful automatic speec...
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11/19/2018
The PyTorch-Kaldi Speech Recognition Toolkit
The availability of open-source software is playing a remarkable role in...
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07/29/2018
Speaker Recognition from raw waveform with SincNet
Deep learning is progressively gaining popularity as a viable alternativ...
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06/12/2018
Quaternion Recurrent Neural Networks
Recurrent neural networks (RNNs) are powerful architectures to model seq...
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05/26/2018
Automatic context window composition for distant speech recognition
Distant speech recognition is being revolutionized by deep learning, tha...
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04/15/2018
Twin Regularization for online speech recognition
Online speech recognition is crucial for developing natural human-machin...
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03/26/2018
Light Gated Recurrent Units for Speech Recognition
A field that has directly benefited from the recent advances in deep lea...
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12/17/2017
Deep Learning for Distant Speech Recognition
Deep learning is an emerging technology that is considered one of the mo...
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11/26/2017
Realistic multi-microphone data simulation for distant speech recognition
The availability of realistic simulated corpora is of key importance for...
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10/11/2017
Audio Concept Classification with Hierarchical Deep Neural Networks
Audio-based multimedia retrieval tasks may identify semantic information...
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10/10/2017
Contaminated speech training methods for robust DNN-HMM distant speech recognition
Despite the significant progress made in the last years, state-of-the-ar...
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10/06/2017
The DIRHA-English corpus and related tasks for distant-speech recognition in domestic environments
This paper introduces the contents and the possible usage of the DIRHA-E...
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09/29/2017
Improving speech recognition by revising gated recurrent units
Speech recognition is largely taking advantage of deep learning, showing...
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03/24/2017
Batch-normalized joint training for DNN-based distant speech recognition
Improving distant speech recognition is a crucial step towards flexible ...
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03/23/2017