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/

Global: Zendy Tools annual

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

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Previous speech enhancement methods focus on estimating the short-timespectrum of speech signals due to its short-term stability. However, thesemethods often only estimate the clean magnitude spectrum and reuse the noisyphase when resynthesize speech signals, which is unlikely a valid short-timeFourier transform (STFT). Recently, DNN based speech enhancement methods mainlyjoint estimation of the magnitude and phase spectrum. These methods usuallygive better performance than magnitude spectrum estimation but need much largercomputation and memory overhead. In this paper, we propose using the DiscreteCosine Transform (DCT) to reconstruct a valid short-time spectrum. Under theU-net structure, we enhance the real spectrogram and finally achieve perfectperformance.

End-to-end speech enhancement based on discrete cosine transform