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

This study presents a large scale benchmarking on cloud based Speech-To-Textsystems: {Google Cloud Speech-To-Text}, {Microsoft Azure Cognitive Services},{Amazon Transcribe}, {IBM Watson Speech to Text}. For each systems, 40158 cleanand noisy speech files about 101 hours are tested. Effect of background noiseon STT quality is also evaluated with 5 different Signal-to-noise ratios from40dB to 0dB. Results showed that {Microsoft Azure} provided lowesttranscription error rate $9.09\%$ on clean speech, with high robustness tonoisy environment. {Google Cloud} and {Amazon Transcribe} gave similarperformance, but the latter is very limited for time-constraint usage. Though{IBM Watson} could work correctly in quiet conditions, it is highly sensible tonoisy speech which could strongly limit its application in real lifesituations.

A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect