VoiceInteraction

VoiceInteraction

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Established in 2008, VoiceInteraction is now a global software company that provides speech processing-based solutions for the TV Broadcast Industry. Bringing speech knowledge to the center of our solutions has always been our vision and that allows us to be recognized as one of major world-wide providers in this field. With proprietary technology based on AI and Machine Learning, our expertise relies on Automatic Closed Captioning software for live shows, offline transcription and Compliance/Media Discovery Systems. Having our origins in the Academia, we strive for constant innovation: our time is spent researching and developing new and more effective ways of unveiling the underlying knowledge of media contents.

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Tag: Closed captioning

VoiceInteraction

Established in 2008, VoiceInteraction is now a global software company that provides speech processing-based solutions for the TV Broadcast Industry. Bringing speech knowledge to the center of our solutions has always been our vision and that allows us to be recognized as one of major world-wide providers in this field. With proprietary technology based on AI and Machine Learning, our expertise relies on Automatic Closed Captioning software for live shows, offline transcription and Compliance/Media Discovery Systems. Having our origins in the Academia, we strive for constant innovation: our time is spent researching and developing new and more effective ways of unveiling the underlying knowledge of media contents.

Enabling AI-powered Transcription, Closed Captioning, and Translation With Elevated Speed and Efficiency for a Leading Provider of Entertainment Content

Consumers’ insatiable and growing demand for streaming media on ever-greater numbers of OTT platforms offers fantastic opportunities, as well as daunting challenges, for content providers. The goal is to deliver high-value content tailored to the specific requirements of each platform, including multi-language transcriptions and compliant closed captions, and to do it as fast and efficiently as possible. Speed and efficiency are especially important in a news and entertainment environment, where every second counts in delivering breaking stories. As one of the premier entertainment news sites with a focus on Hollywood, this Digital Nirvana client recently signed on as a short-form content provider for Quibi.

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Current Applications of Machine Learning and Artificial Intelligence in M&E

While the impact of ML and AI have been discussed and debated for years, practical applications are fast accelerating across the media supply chain. The pace of innovation is moving quickly and with the cloud wars in full force, there are new services becoming available all the time that offer novel ways to automate tasks with ML and AI. Already, the big three cloud providers — AWS, Azure, and Google — have rolled out powerful capabilities that help with essential tasks including captioning, transcription, and even object/facial recognition to bolster compliance edits and to augment metadata. For media organizations, the implications of these solutions are vast, and we’ve already begun to see their power.  With things moving so fast, though, it’s challenging to keep up and important to have the right architecture and structure in place to take advantage of these innovations.

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Mediaproxy Whitepaper: Take Control of OTT Monitoring

OTT has become increasingly popular with viewers and is an important form of distribution and revenue generation for broadcasters. As these trends continue, content owners and regulators alike are looking to apply the same standards for video, audio, and captioning to OTT as with traditional television.
For OTT services, broadcast engineers need to ensure compliance and quality of service for live content viewed on multiple devices that rely on multiple ABR formats each with several profiles. Keeping up with this complexity can be daunting, which is why having a unified system for monitoring compliance and identifying issues across all traditional and OTT playouts is critical...

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IBM and KTVA Case Study

Manual captioning is time-consuming and costly. KTVA needed to drive efficiency with an automated speech recognition solution that was easily trainable, used AI to learn words in context and continually improved over time.

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