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 Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Brain-to-speech technology represents a fusion of interdisciplinaryapplications encompassing fields of artificial intelligence, brain-computerinterfaces, and speech synthesis. Neural representation learning basedintention decoding and speech synthesis directly connects the neural activityto the means of human linguistic communication, which may greatly enhance thenaturalness of communication. With the current discoveries on representationlearning and the development of the speech synthesis technologies, directtranslation of brain signals into speech has shown great promise. Especially,the processed input features and neural speech embeddings which are given tothe neural network play a significant role in the overall performance whenusing deep generative models for speech generation from brain signals. In thispaper, we introduce the current brain-to-speech technology with the possibilityof speech synthesis from brain signals, which may ultimately facilitateinnovation in non-verbal communication. Also, we perform comprehensive analysison the neural features and neural speech embeddings underlying theneurophysiological activation while performing speech, which may play asignificant role in the speech synthesis works.

Neural Speech Embeddings for Speech Synthesis Based on Deep Generative Networks