Broadcast Beat Magazine 2018 NAB Show Edition - Page 94

captioning solutions for years. ASR offers broadcasters an opportunity to train the engine in the short term and reap the rewards in the long term as accuracy increases with addi- tional content. Machines to the rescue Machine learning is bringing a new dawn of pos- sibilities to the captioning scene. A new genera- tion of cloud-based AI and ML systems are able to analyze, understand and learn the surrounding context of dialog content in much the same way that humans do. Such systems have a chance to succeed where previous captioning-automation platforms have fallen short. Harnessing the power of the cloud, AI-based automated speech recog- nition (ASR) systems are now able to examine and interpret words. Using sophisticated machine learning algorithms, cloud-based ASR engines can help do the transcription work faster and can learn to become more precise. With the ability to self-learn from every correc- tion, recognition accuracy of cloud-based ML automated speech recognition systems improves with each use. Names and proper nouns are automatically extracted from human-reviewed transcription and used as glossary words, ensur- ing they will be recognized and spelled properly in subsequent uses. The key element behind the efficacy of ASR for video content is a machine learning from a human to perform better. And as the accuracy of auto-transcription increases, humans can leverage advanced ASR systems to increase their own productivity When the unlimited horsepower of the cloud is leveraged against the enormous amounts of data being processed and learned from diverse sources, on-the-ground solutions cannot hope to compete. The next generation of cloud-based ASR systems are already working with dozens of languages, and they continue to evolve, learn and adapt as needs change. Missed Opportunity: Machine Learning Broadcasters and ASR engines learn from audio that is already available, but much of the content that is used on TV and film is not yet being utilized to train the speech engines. Different from other broadcast technologies, like transcoding software or rack mount scopes where the software can’t learn from the media content, machine learning for 94 • Broadcast Beat Magazine • Captioning for live and remote streaming During the last few years, the Federal Communications Commission (FCC) has strength- ened its regulations on captioning for internet video programming. All video media previously aired on television must now be captioned when repurposed for online distribution. And most recently, FCC captioning rules have been extend- ed to include live and near-live programming, which must now be captioned for the internet within 8-12 hours from the time of the original broadcast. For now, this rule only applies to content that has appeared on television, but it is inevitable that closed captioning workflows will have to funda- mentally evolve to meet the needs of the ever- increasing live streaming content that consumers demand. Captioning online content sends a mes- sage of inclusion that has a strong positive impact on audience engagement and brand approval. Reading captions also improves content com- prehension, especially second-language viewers, which means your message will come across more clearly. Captioning means more viewers and more engagement and a better understat- ing of your message, regardless of whether the video is playing on a mobile device or on a monitor in a noisy airport terminal or busy sports bar. Captioning also enhances online visibility as search engines can index the text in your video and improves data mining possibilities. By using a cloud-based live restreaming service, accurate captions can be married to the live program in perfect sync, rather than always dis- playing a few seconds behind the video, vastly improving the experience for end users who rely on captions. This is done by adjusting the video latency slightly to account for the delay inherent to all live closed captioning techniques. The future is here Cloud-based ASR solutions are already making their way into modern closed captioning work-