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Related publications (31)

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Thanks to Deep Learning Text-To-Speech (TTS) has achieved high audio quality with large databases. But at the same time the complex models lost any ability to control or interpret the generation process. For the big challenge of affective TTS it is infeasi ...

EPFL2022

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Mathew Magimai Doss, Eklavya Sarkar

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

2022

Learning voice source related information for depression detection

Subrahmanya Pavankumar Dubagunta

During depression neurophysiological changes can occur, which may affect laryngeal control i.e. behaviour of the vocal folds. Characterising these changes in a precise manner from speech signals is a non trivial task, as this typically involves reliable se ...

IEEE2019

End-to-end text-dependent speaker verification using novel distance measures

Petr Motlicek, Subhadeep Dey

This paper explores novel ideas in building end-to-end deep neural network (DNN) based text-dependent speaker verification (SV) system. The baseline approach consists of mapping a variable length speech segment to a fixed dimensional speaker vector by esti ...

2018

Recent advances in high-harmonic generation gave rise to soft X-ray pulses with higher intensity, shorter duration and higher photon energy. One of the remaining shortages of this source is its restriction to linear polarization, since the yield of generat ...

Nature Publishing Group2015

, ,

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

Incremental Syllable-Context Phonetic Vocoding

Petr Motlicek, Philip Neil Garner, Milos Cernak

2015

Combining Vocal Tract Length Normalization with Hierarchical Linear Transformations

Philip Neil Garner, John David Scott Dines, Lakshmi Babu Saheer

Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis. VTLN produces speech with naturalness preferable to that of MLLR-based adaptation tec ...

2014

Joint Source-Filter Optimization for Accurate Vocal Tract Estimation Using Differential Evolution

Jean-Marc Vesin, Olaf Schleusing

In this work, we present a joint source-filter optimization approach for separating voiced speech into vocal tract (VT) and voice source components. The presented method is pitch-synchronous and thereby exhibits a high robustness against vocal jitter, shim ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Source/Filter Factorial Hidden Markov Model, with Application to Pitch and Formant Tracking

Jean-Philippe Thiran

Tracking vocal tract formant frequencies (

f_p

) and estimating the fundamental frequency (

f_0

) are two tracking problems that have been tackled in many speech processing works, often independently, with applications to articulatory parameters estimation ...

Institute of Electrical and Electronics Engineers2013