The use of neural networks in speech synthesis has been especially successful in the domain of prosody generation. The approach presented here differs from others in a) the transformation from a simple input to an output vector consisting of different parameters and b) the use of subcorpora that allow specialized networks. The network operates in a prominence-based synthesis system, where prominence is the most important parameter and is, consequently, the input parameter for the network. The output is not yet evaluated formally but the synthetic speech sounds natural and lively
This paper describes the neural network algorithm flexibly incorporated into the text-to-speech (TTS...
Windmann A, Wagner P, Tamburini F, Arnold D, Oertel C. Automatic Prominence Annotation of a German S...
Vocal emotions, as well as different speaking styles and speaker traits, are characterized by a comp...
The use of neural networks in speech synthesis has been especially successful in the domain of proso...
This contribution describes the programme for one part of the automatic Text-to-Speech (TTS) synthes...
The absence of convincing intonation makes current parametric speech synthesis systems sound dull a...
This contribution describes the programme for one part of theautomatic Text-to-Speech (TTS) synthesi...
This research was accomplished during my studies at University of Sussex under supervision of Dr Si ...
Statistical parametric speech synthesis (SPSS) has seen improvements over recent years, especially ...
A neural net based speech synthesis project is discussed. The novelty is that the reproduced speech ...
Baumann T, Schlangen D. Evaluating Prosodic Processing for Incremental Speech Synthesis. In: Procee...
In this paper, we develop a speech learning machine by using Neural-Network. The work is based on a ...
This thesis proposes to improve and enrich the expressiveness of English Text-to-Speech (TTS) synthe...
End-to-end text-to-speech synthesis systems achieved immense success in recent times, with improved ...
Windmann A, Wagner P, Tamburini F, Arnold D, Oertel C. Automatic Prominence Annotation of a German S...
This paper describes the neural network algorithm flexibly incorporated into the text-to-speech (TTS...
Windmann A, Wagner P, Tamburini F, Arnold D, Oertel C. Automatic Prominence Annotation of a German S...
Vocal emotions, as well as different speaking styles and speaker traits, are characterized by a comp...
The use of neural networks in speech synthesis has been especially successful in the domain of proso...
This contribution describes the programme for one part of the automatic Text-to-Speech (TTS) synthes...
The absence of convincing intonation makes current parametric speech synthesis systems sound dull a...
This contribution describes the programme for one part of theautomatic Text-to-Speech (TTS) synthesi...
This research was accomplished during my studies at University of Sussex under supervision of Dr Si ...
Statistical parametric speech synthesis (SPSS) has seen improvements over recent years, especially ...
A neural net based speech synthesis project is discussed. The novelty is that the reproduced speech ...
Baumann T, Schlangen D. Evaluating Prosodic Processing for Incremental Speech Synthesis. In: Procee...
In this paper, we develop a speech learning machine by using Neural-Network. The work is based on a ...
This thesis proposes to improve and enrich the expressiveness of English Text-to-Speech (TTS) synthe...
End-to-end text-to-speech synthesis systems achieved immense success in recent times, with improved ...
Windmann A, Wagner P, Tamburini F, Arnold D, Oertel C. Automatic Prominence Annotation of a German S...
This paper describes the neural network algorithm flexibly incorporated into the text-to-speech (TTS...
Windmann A, Wagner P, Tamburini F, Arnold D, Oertel C. Automatic Prominence Annotation of a German S...
Vocal emotions, as well as different speaking styles and speaker traits, are characterized by a comp...