Cloud-Based Analytics for Voice-to-Text Overview

Purpose

Utilizing A.I. and machine learning to generate accurate, descriptive text from speech in real time or near-real time. 

Big Picture 

A.I. and cloud-based analytics are becoming the standard in text accessibility everywhere. More and more companies are utilizing machine learning to generate closed captioning to increase engagement, from deaf and hard-of-hearing individuals to some who simply prefer to watch without sound in particular settings. Speech-to-text software has come a long way, but there are still some hurdles such as juxtaposed languages or garbled speech which it cannot yet decode – which is where A.I. and machine learning are focused on building their knowledge bases. 

Scope of Analysis 

The examination of this sector is limited to smart text generation using cloud-based analytics. Patents specifically related to eliminating latency or errors in accuracy with streaming were mainly of interest. 

Tags and Their Meaning 

Hardware

Apparatus:  Physical apparatus for accessibility

Bluetooth: Voice-to-text generator utilizing Bluetooth devices

Remote: Accessibility advancing features available through remote control, or modified remote design to accommodate these.

Processing

Reconciliation: Improving audio and video synchronization

Metadata: Automated pulling of data from archived previous broadcasts

Streaming: Real-time closed captioning for live broadcasts

A.I. 

Search: Cloud based analytics to locate context for a program in order to generate closed captioning

Learning: Software that can adapt and improve its transcribing abilities utilizing tagging

Applications

Language: Focusing on closed captioning and subtitles as a method to facilitate language learning for non-native speakers

Advertisements: Inputting closed captioning to improve Search Engine Optimization (SEO), as well as accessibility

User Interface: Advanced user-friendly controls for personalized subtitle/closed captioning display