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Robust Speech Recognition and Feature Extraction Using HMM2

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Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

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

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

Language Independent Query by Example Spoken Term Detection

Dhananjay Ram

Language independent query-by-example spoken term detection (QbE-STD) is the problem of retrieving audio documents from an archive, which contain a spoken query provided by a user. This is usually casted as a hypothesis testing and pattern matching problem ...

EPFL2019

Combining the SNR Spectrum with a Cochlear Model

Philip Neil Garner

The SNR spectrum was previously introduced as a natural consequence of using cepstral normalisa- tion in speech recognition; it is closely related to the articulation index of Fletcher. Motivated initially by a theoretical difficulty in frequency warping, ...

Idiap2018

Towards End-to-End Speech Recognition

Dimitri Palaz

Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, ...

EPFL2016

Privacy-Sensitive Audio Features for Conversational Speech Processing

Sree Hari Krishnan Parthasarathi

The work described in this thesis takes place in the context of capturing real-life audio for the analysis of spontaneous social interactions. Towards this goal, we wish to capture conversational and ambient sounds using portable audio recorders. Analysis ...

EPFL2011

Privacy-Sensitive Audio Features for Conversational Speech Processing

Sree Hari Krishnan Parthasarathi

Ecole Polytechnique Fédérale de Lausanne2011

Boosting Localized Features for Speaker and Speech Recognition

Anindya Roy

In this thesis, we propose a novel approach for speaker and speech recognition involving localized, binary, data-driven features. The proposed approach is largely inspired by similar localized approaches in the computer vision domain. The success of these ...

EPFL2011

Boosting Localized Features for Speaker and Speech Recognition

Anindya Roy

Ecole Polytechnique Federale de Lausanne (EPFL)2011

Privacy-Sensitive Audio Features for Speech/Nonspeech Detection

Hervé Bourlard, Daniel Gatica-Perez, Sree Hari Krishnan Parthasarathi

The goal of this paper is to investigate features for speech/nonspeech detection (SND) having ``minimal'' linguistic information from the speech signal. Towards this, we present a comprehensive study of privacy-sensitive features for SND in multiparty conv ...

Idiap2011