4 posts tagged with "Captioning"

California Senate Bill 707 is the most significant update to the state's open meeting law in decades. Signed by Governor Newsom on October 3, 2025, SB 707 amends the Ralph M. Brown Act to require public agencies across California to offer hybrid meetings with two-way remote participation, activate real-time captioning on video platforms, translate meeting agendas into languages spoken by significant portions of the local population, and take concrete steps to encourage participation from underrepresented communities. The law took effect on January 1, 2026, with enhanced requirements for larger agencies kicking in on July 1, 2026.

A question we hear constantly from organizations managing large video libraries: "We need a way to measure the accuracy and consistency of captions across our library of training videos. They've been created by folks across the organization, so quality varies. Does anyone use a tool for this?"

The short answer: yes, and Recap has it built in. Here's how Word Error Rate tooling works and why it matters when caption quality varies across your team.

Procurement officers and accessibility coordinators evaluating captioning vendors often see claims of "99% accuracy" or "WER under 1%." But caption quality involves more than word-level accuracy. Formatted Error Rate (FER) and Word Error Rate (WER) measure different aspects of caption quality. Understanding both metrics helps you specify the right quality requirements in RFPs and evaluate vendor performance. This guide explains the technical definitions, when each metric applies, and what to request from vendors.

Ensuring that video-based content is accessible to all learners is increasingly important in online learning environments. Video transcription, closed-captions, translation, and audio description are essential tools for addressing barriers faced by students with hearing and sight impairments, non-native speakers, and those who benefit from text-based learning. This article outlines best practices for integrating these tools into online learning environments, with a focus on how AI technologies can streamline and enhance the process, while also incorporating human-generated transcripts for added accuracy.