English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

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.

Speaking Style Conversion from Normal to Lombard Speech Using a Glottal Vocoder and Bayesian GMMs