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Fast keyword detection with sparse time-frequency models

Publications associées (33)

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Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Automatic pathological speech assessment

Parvaneh Janbakhshi

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

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Although current trends in speech processing consider deep learning through data-driven technologies, many potential applications exhibit lack of training or development data. Therefore, considerably light signal processing techniques are still of interest ...

Idiap2020

Understanding and Visualizing Raw Waveform-based CNNs

Sébastien Marcel, Hannah Muckenhirn

Modeling directly raw waveforms through neural networks for speech processing is gaining more and more attention. Despite its varied success, a question that remains is: what kind of information are such neural networks capturing or learning for different ...

2019

This thesis deals with exploiting the low-dimensional multi-subspace structure of speech towards the goal of improving acoustic modeling for automatic speech recognition (ASR). Leveraging the parsimonious hierarchical nature of speech, we hypothesize that ...

EPFL2019

End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

Ronan Collobert, Dimitri Palaz

In hidden Markov model (HMM) based automatic speech recognition (ASR) system, modeling the statistical relationship between the acoustic speech signal and the HMM states that represent linguistically motivated subword units such as phonemes is a crucial st ...

ELSEVIER SCIENCE BV2019

Spectral Subspace Analysis for Automatic Assessment of Pathological Speech Intelligibility

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Speech intelligibility is an important assessment criterion of the communicative performance of pathological speakers. To assist clinicians in their assessment, time- and cost-efficient automatic intelligibility measures offering a repeatable and reliable ...

2019

AM-FM DECOMPOSITION OF SPEECH SIGNAL: APPLICATIONS FOR SPEECH PRIVACY AND DIAGNOSIS

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Amrutha Prasad

2019

Phonetic Subspace Features for Improved Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

This paper addresses the problem of detecting speech utterances from a large audio archive using a simple spoken query, hence referring to this problem as "Query by Example Spoken Term Detection" (QbE-STD). This still open pattern matching problem has been ...

2018

Gradient-based spectral visualization of CNNs using raw waveforms

Sébastien Marcel, Hannah Muckenhirn

Modeling directly raw waveform through neural networks for speech processing is gaining more and more attention. Despite its varied success, a question that remains is: what kind of information are such neural networks capturing or learning for different t ...

Idiap2018