Publication

Personalising speech-to-speech translation in the EMIME project

Related publications (33)

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

EPFL2021

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

Trustworthy speaker recognition with minimal prior knowledge using neural networks

Hannah Muckenhirn

The performance of speaker recognition systems has considerably improved in the last decade. This is mainly due to the development of Gaussian mixture model-based systems and in particular to the use of i-vectors. These systems handle relatively well noise ...

EPFL2019

Improving Children Speech Recognition through Feature Learning from Raw Speech Signal

Selen Hande Kabil, Subrahmanya Pavankumar Dubagunta

Children speech recognition based on short-term spectral features is a challenging task. One of the reasons is that children speech has high fundamental frequency that is comparable to formant frequency values. Furthermore, as children grow, their vocal ap ...

IEEE2019

Intonation Modelling for Speech Synthesis and Emphasis Preservation

Pierre-Edouard Jean Charles Honnet

Speech-to-speech translation is a framework which recognises speech in an input language, translates it to a target language and synthesises speech in this target language. In such a system, variations in the speech signal which are inherent to natural hum ...

EPFL2017

, , , ,

In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for ...

2013

Unified Framework of Feature Based Adaptation for Statistical Speech Synthesis and Recognition

Lakshmi Babu Saheer

The advent of statistical parametric speech synthesis has paved new ways to a unified framework for hidden Markov model (HMM) based text to speech synthesis (TTS) and automatic speech recognition (ASR). The techniques and advancements made in the field of ...

EPFL2013

A Savitzky-Golay Filtering Perspective of Dynamic Feature Computation

Mathew Magimai Doss, Chandra Sekhar Seelamantula

We address the classical problem of delta feature computation, and interpret the operation involved in terms of Savitzky-Golay (SG) filtering. Features such as the mel-frequency cepstral coefficients (MFCCs), obtained based on short-time spectra of the spe ...

2013

Unified Framework Of Feature Based Adaptation For Statistical Speech Synthesis And Recognition

Lakshmi Babu Saheer

Ecole Polytechnique Federale de Lausanne (EPFL)2012

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