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On Use of Task Independent Training Data in Tandem Feature Extraction

Related publications (32)

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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

Mining, Modeling and Predicting Mobility

Mohamed Kafsi

Mobility is a central aspect of our life, and our movements reveal much more about us than simply our whereabouts. In this thesis, we are interested in mobility and study it from three different perspectives: the modeling perspective, the information-theor ...

EPFL2015

Statistical models for HMM/ANN hybrids

Philip Neil Garner, David Imseng

We present a theoretical investigation into the use of normalised artificial neural network (ANN) outputs in the context of hidden Markov models (HMMs). The work is motivated by the pursuit of a more theoretically rigorous understanding of the Kullback-Lie ...

Idiap2013

Markov chains with discontinuous drifts have differential inclusion limits

Nicolas Gabriel Gast

In this paper, we study deterministic limits of Markov processes having discontinuous drifts. While most results assume that the limiting dynamics is continuous, we show that these conditions are not necessary to prove convergence to a deterministic system ...

Elsevier2012

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

Enhanced Phone Posteriors for Improving Speech Recognition Systems

Hervé Bourlard, Hamed Ketabdar

Using phone posterior probabilities has been increasingly explored for improving automatic speech recognition (ASR) systems. In this paper, we propose two approaches for hierarchically enhancing these phone posteriors, by integrating long acoustic context, ...

2010

Measuring the gap between HMM-based ASR and TTS

John David Scott Dines, Simon King

The EMIME European project is conducting research in the development of technologies for mobile, personalised speech-tospeech translation systems. The hidden Markov model is being used as the underlying technology in both automatic speech recognition (ASR) ...

2009

Measuring the gap between HMM-based ASR and TTS

John David Scott Dines, Simon King

Idiap2009

Spectro-Temporal Features for Automatic Speech Recognition using Linear Prediction in Spectral Domain

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Frequency Domain Linear Prediction (FDLP) provides an efficient way to represent temporal envelopes of a signal using auto-regressive models. For the input speech signal, we use FDLP to estimate temporal trajectories of sub-band energy by applying linear p ...

2008