Paper Info
Title
Speaking Style Conversion From Normal To Lombard Speech Using A Glottal Vocoder And Bayesian Gmms
Abstract
Speaking style conversion is the technology of converting natural speech signals from one style to another. In this study, we focus on normal-to-Lombard conversion. This can be used, for example. to enhance the intelligibility of speech in noisy environments. We propose a parametric approach that uses a vocoder to extract speech features. These features are mapped using Bayesian GMMs from utterances spoken in normal style to the corresponding features of Lombard speech. Finally. the mapped features are converted to a Lombard speech waveform with the vocoder. Two vocoders were compared in the proposed normal-to-Lombard conversion: a recently developed glottal vocoder that decomposes speech into glottal flow excitation and vocal tract, and the widely used STRAIGHT vocoder. The conversion quality was evaluated in two subjective listening tests measuring subjective similarity and naturalness. The similarity test results show that the system is able to convert normal speech into Lombard speech for the two vocoders. However, the subjective naturalness of the converted Lombard speech was clearly better using the glottal vocoder in comparison to STRAIGHT.
Year
DOI
Venue
2017
10.21437/Interspeech.2017-400
18TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2017), VOLS 1-6: SITUATED INTERACTION
Keywords
Field
DocType
speaking style conversion, vocal effort, Lombard speech, glottal vocoder, Bayesian GMM
Computer science,Speech recognition,Speaking style,Bayesian probability
Conference
ISSN
Citations 
PageRank 
2308-457X
3
0.44
References 
Authors
7
5
Name
Order
Citations
PageRank
Ana Ramírez López141.17
Shreyas Seshadri263.19
Lauri Juvela3358.29
Okko Johannes Räsänen49914.30
Paavo Alku572898.07