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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This research presents a novel algorithm for detecting human emotion via speech recognition by using speech spectrogram. The proposed algorithm aims to detect the emotional by using information inside the spectrogram. Neural network was used for being the classifier. A new approach to feature extraction based on analysis of two dimensions time-frequency representation of a speech signal have been presented. The algorithm was tested with EMO-Database. The experimental results show that the proposed framework can efficiently find the correct speech emotion compared to using the traditional methods.

Use of Neural Network Classifier for Detecting Human Emotion via Speech Spectrogram