5 citations · 7 across the 6 of their papers we have counts for
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Efficient training strategies for natural sounding speech synthesis and speaker adaptation based on FastPitch
Teodora Răgman, Adriana Stan
This paper focuses on adapting the functionalities of the FastPitch model to the Romanian language; extending the set of speakers from one to eighteen; synthesising speech using an…
TBDM-Net: Bidirectional Dense Networks with Gender Information for Speech Emotion Recognition
Vlad Striletchi, Cosmin Striletchi, Adriana Stan
This paper presents a novel deep neural network-based architecture tailored for Speech Emotion Recognition (SER). The architecture capitalises on dense interconnections among multi…
An analysis of large speech models-based representations for speech emotion recognition
Adrian Bogdan Stânea, Vlad Striletchi, Cosmin Striletchi +1
Large speech models-derived features have recently shown increased performance over signal-based features across multiple downstream tasks, even when the networks are not finetuned…
FlexLip: A Controllable Text-to-Lip System
Dan Oneata, Beata Lorincz, Adriana Stan +1
The task of converting text input into video content is becoming an important topic for synthetic media generation. Several methods have been proposed with some of them reaching cl…
An objective evaluation of the effects of recording conditions and speaker characteristics in multi-speaker deep neural speech synthesis
Beata Lorincz, Adriana Stan, Mircea Giurgiu
Multi-speaker spoken datasets enable the creation of text-to-speech synthesis (TTS) systems which can output several voice identities. The multi-speaker (MSPK) scenario also enable…
Speaker verification-derived loss and data augmentation for DNN-based multispeaker speech synthesis
Beata Lorincz, Adriana Stan, Mircea Giurgiu
Building multispeaker neural network-based text-to-speech synthesis systems commonly relies on the availability of large amounts of high quality recordings from each speaker and co…