Publications de Milos Cernak | EPFL Graph Search

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

Hervé Bourlard, Milos Cernak, Afsaneh Asaei

The speech signal conveys information on different time scales from short (20–40 ms) time scale or segmental, associated to phonological and phonetic information to long (150–250 ms) time scale or supra segmental, associated to syllabic and prosodic inform ...

Idiap2016

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

Hervé Bourlard, Milos Cernak, Afsaneh Asaei

The speech signal conveys information on different time scales from short (20--40 ms) time scale or segmental, associated to phonological and phonetic information to long (150--250 ms) time scale or supra segmental, associated to syllabic and prosodic info ...

2016

Phonological Vocoding Using Artificial Neural Networks

Philip Neil Garner, Milos Cernak

We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...

IEEE2015

Phonological vocoding using artificial neural networks

Philip Neil Garner, Milos Cernak

We investigate a vocoder based on artificial neural networks using a phonological speech representation. Speech decomposition is based on the phonological encoders, realised as neural network classifiers, that are trained for a particular language. The spe ...

Idiap2015

Incremental Syllable-Context Phonetic Vocoding

Petr Motlicek, Philip Neil Garner, Milos Cernak

Current very low bit rate speech coders are, due to complexity limitations, designed to work off-line. This paper investigates incremental speech coding that operates real-time and incrementally (i.e., encoded speech depends only on already-uttered speech ...

Idiap2015

HMM-based Non-native Accent Assessment using Posterior Features

Milos Cernak, Ramya Rasipuram

Automatic non-native accent assessment has many potential benefits in language learning and speech technologies. The three fundamental challenges in automatic accent assessment are to characterize, model and assess individual variation in speech of the non ...

Idiap2015

Incremental Syllable-Context Phonetic Vocoding

Petr Motlicek, Philip Neil Garner, Milos Cernak

Current very low bit rate speech coders are, due to complexity limitations, designed to work off-line. This paper investigates incremental speech coding that operates real-time and incrementally (i.e., encoded speech depends only on already-uttered speech ...

2015

Syllabic Pitch Tuning for Neutral-to-Emotional Voice Conversion

Milos Cernak, Lakshmi Babu Saheer

Prosody plays an important role in both identification and synthesis of emotionalized speech. Prosodic features like pitch are usually estimated and altered at a segmental level based on short windows of speech (where the signal is expected to be quasi-sta ...

Idiap2015

A simple continuous excitation model for parametric vocoding

Philip Neil Garner, Milos Cernak

We describe a continuous-pitch parametric vocoder suitable for speech coding and statistical text to speech synthesis. The spectral model is based on linear prediction. We show that glottal modelling techniques from recent literature can be cherry-picked t ...

Idiap2015

Speech vocoding for laboratory phonology

Milos Cernak

In this paper, we propose a platform based on phonological speech vocoding for examining relations between phonology and speech processing, and in broader terms, between the abstract and physical structures of speech signal. The goal of this paper is to go ...

Idiap2015

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On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

Phonological Vocoding Using Artificial Neural Networks

Phonological vocoding using artificial neural networks

Incremental Syllable-Context Phonetic Vocoding

HMM-based Non-native Accent Assessment using Posterior Features

Incremental Syllable-Context Phonetic Vocoding

Syllabic Pitch Tuning for Neutral-to-Emotional Voice Conversion

A simple continuous excitation model for parametric vocoding

Speech vocoding for laboratory phonology

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

Incremental Syllable-Context Phonetic Vocoding

HMM-based Non-native Accent Assessment using Posterior Features

A simple continuous excitation model for parametric vocoding

Syllabic Pitch Tuning for Neutral-to-Emotional Voice Conversion

Incremental Syllable-Context Phonetic Vocoding

Phonological vocoding using artificial neural networks

Speech vocoding for laboratory phonology

Phonological Vocoding Using Artificial Neural Networks