Emotion conversion based on prosodic unit selection

Authors:
Daniel Erro;Eva Navas;Inma Hernáez;Ibon Saratxaga
Affiliations:
AhoLab Signal Processing Laboratory, Electronics and Telecommunications Department, University of the Basque Country, AIda, Bilbao, Spain;AhoLab Signal Processing Laboratory, Electronics and Telecommunications Department, University of the Basque Country, AIda, Bilbao, Spain;AhoLab Signal Processing Laboratory, Electronics and Telecommunications Department, University of the Basque Country, AIda, Bilbao, Spain;AhoLab Signal Processing Laboratory, Electronics and Telecommunications Department, University of the Basque Country, AIda, Bilbao, Spain
Venue:
IEEE Transactions on Audio, Speech, and Language Processing
Year:
2010

Citing 9
Cited 1

Voice transformation using PSOLA technique

Speech Communication - Eurospeech '91
Analysis and synthesis of German F0 contours by means of Fujisaki's model

Speech Communication - Special issue: Fujisaki's Festschrift
Transformation of formants for voice conversion using artificial neural networks

Speech Communication - Special issue: voice conversion: state of the art and perspectives
High-resolution voice transformation

High-resolution voice transformation
Unit selection in a concatenative speech synthesis system using a large speech database

ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Conversion Function Clustering and Selection Using Linguistic and Spectral Information for Emotional Voice Conversion

IEEE Transactions on Computers
Data-driven emotion conversion in spoken English

Speech Communication
Prosody conversion from neutral speech to emotional speech

IEEE Transactions on Audio, Speech, and Language Processing
Quality-enhanced voice morphing using maximum likelihood transformations

IEEE Transactions on Audio, Speech, and Language Processing

Production of filled pauses in concatenative speech synthesis based on the underlying fluent sentence

Speech Communication

Quantified Score

Hi-index	0.00

Visualization

Abstract

Voice conversion has been traditionally focused on spectrum. Current systems lack a solid prosody conversion method suitable for different speaking styles. Recently, the unit selection technique has been applied to transform emotional intonation contours. This paper goes one step beyond: it explores strategies for training and configuring the selection cost function in an emotion conversion application. The proposed system, which uses accent groups as basic intonation units and performs conversion also on phoneme durations and intensity, is evaluated by means of a carefully designed subjective test involving the big six emotions. Although the expressiveness of the converted sentences is still far from that of natural emotional speech, satisfactory results are obtained when different configurations are used for different emotions.