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Hynek Hermansky

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Related publications (114)

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

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Amrutha Prasad

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

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

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy, Amrutha Prasad

2019

Phase AutoCorrelation (PAC) features for noise robust speech recognition

Hynek Hermansky, Hemant Misra, Shajith Ikbal

In this paper, we introduce a new class of noise robust features derived from an alternative measure of autocorrelation representing the phase variation of speech signal frame over time. These features, referred to as Phase AutoCorrelation (PAC) features i ...

2012

Analysis of MLP Based Hierarchical Phoneme Posterior Probability Estimator

Hervé Bourlard, Hynek Hermansky, Joel Praveen Pinto

We analyze a simple hierarchical architecture consisting of two multilayer perceptron (MLP) classifiers in tandem to estimate the phonetic class conditional probabilities. In this hierarchical setup, the first MLP classifier is trained using standard acous ...

2010

Autoregressive Models of Amplitude Modulations in Audio Compression

Petr Motlicek, Hynek Hermansky, Sriram Ganapathy

We present a scalable medium bit-rate wide-band audio coding technique based on frequency domain linear prediction (FDLP). FDLP is an efficient method for representing the long-term amplitude modulations of speech/audio signals using autoregressive models. ...

2010

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We revisit an original concept of speech coding in which the signal is separated into the carrier modulated by the signal envelope. A recently developed technique, called frequency-domain linear prediction (FDLP), is applied for the efficient estimation of ...

2010

The DIRAC AWEAR Audio-Visual Platform for Detection of Unexpected and Incongruent Events

Petr Motlicek, Hynek Hermansky, Barbara Caputo, Jie Luo

It is of prime importance in everyday human life to cope with and respond appropriately to events that are not foreseen by prior experience. Machines to a large extent lack the ability to respond appropriately to such inputs. An important class of unexpect ...

Idiap2010

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Frequency Domain Linear Prediction (FDLP) represents a technique for auto-regressive modelling of Hilbert envelopes of a signal. In this paper, we propose a speech coding technique that uses FDLP in Quadrature Mirror Filter (QMF) sub-bands of short segment ...

Springer - Verlag, Berlin Heidelberg 20092009

Volterra Series for Analyzing MLP based Phoneme Posterior Probability Estimator

Hynek Hermansky, Joel Praveen Pinto

We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. The identified Volterra kernels reveal the spectro-temporal patterns that are l ...

2009

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We present a new feature extraction technique for phoneme recognition that uses short-term spectral envelope and modulation frequency features. These features are derived from sub-band temporal envelopes of speech estimated using Frequency Domain Linear Pr ...

Idiap2009