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Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-specific Scaling

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Multimode optical fiber transmission with a deep learning network

Demetri Psaltis, Christophe Moser, Damien Claude-Marie Loterie, Babak Rahmani, Georgia Konstantinou

Multimode fibers (MMFs) are an example of a highly scattering medium, which scramble the coherent light propagating within them to produce seemingly random patterns. Thus, for applications such as imaging and image projection through an MMF, careful measur ...

CHINESE ACAD SCIENCES, CHANGCHUN INST OPTICS FINE MECHANICS AND PHYSICS2018

Over these last few years, the use of Artificial Neural Networks (ANNs), now often referred to as deep learning or Deep Neural Networks (DNNs), has significantly reshaped research and development in a variety of signal and information processing tasks. Whi ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

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Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be h ...

2018

Joint Localization and Classification of Multiple Sound Sources Using a Multi-task Neural Network

Jean-Marc Odobez, Petr Motlicek, Weipeng He

We propose a novel multi-task neural network-based approach for joint sound source localization and speech/non-speech classification in noisy environments. The network takes raw short time Fourier transform as input and outputs the likelihood values for th ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Markerless tracking of user-defined features with deep learning

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Pranav Mamidanna

2018

DNN based speaker embedding using content information for text-dependent speaker verification

Petr Motlicek, Subhadeep Dey

In this paper, we are interested in exploring Deep Neural Network (DNN) based speaker embedding for Random-digit task using content information. To this end, a technique is applied to automatically select common phonetic units between the enrollment and te ...

2018

Analysis of Language Dependent Front-End for Speaker Recognition

Petr Motlicek, Subhadeep Dey

In Deep Neural Network (DNN) i-vector based speaker recognition systems, acoustic models trained for Automatic Speech Recognition are employed to estimate sufficient statistics for i-vector modeling. The DNN based acoustic model is typically trained on a w ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Towards directly modeling raw speech signal for speaker verification using CNNs

Sébastien Marcel, Hannah Muckenhirn

Speaker verification systems traditionally extract and model cepstral features or filter bank energies from the speech signal. In this paper, inspired by the success of neural network-based approaches to model directly raw speech signal for applications su ...

IEEE2018

Knowledge Transfer with Jacobian Matching

François Fleuret, Suraj Srinivas

Classical distillation methods transfer representations from a “teacher” neural network to a “student” network by matching their output activations. Recent methods also match the Jacobians, or the gradient of output activations with the input. However, thi ...

2018

Fast Language Adaptation Using Phonological Information

Hervé Bourlard, Philip Neil Garner, Sibo Tong

Phoneme-based multilingual connectionist temporal classification (CTC) model is easily extensible to a new language by concatenating parameters of the new phonemes to the output layer. In the present paper, we improve cross-lingual adaptation in the contex ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018