Automate and expedite the QC of Audio, Video, and Caption/Subtitle assets with our on-premise and cloud native QC solutions. Our customers include large studios, broadcasters, or OTT service provider to Post Production houses and smaller boutique media processing entities.
For more details:- https://www.veneratech.com/
Automated Video QC solution
Dive into the world of innovation in automated QC with these captivating videos! From groundbreaking technologies to future possibilities, this is a journey you don’t want to miss. Click the link and join us on an inspiring talk with Venera’s Chief Business Development Officer, Fereidoon Khosravi on what’s new in automated QC tools, CapMate, Pulsar, and Quasar.
Venera Technologies provides cutting-edge file-based QC solutions to the digital media industry, tailored to the evolving requirements of its customers and the industry. Venera’s mission is to improve the operational efficiency of professional content workflows by helping automate time-consuming, tedious content QC operations. Venera’s suite of QC solutions is used by some of the largest Media companies in the world, as well as several smaller boutique post houses and production companies.
Originally Published at:- https://youtu.be/iBXlpoZNZB0?si=faHqxXhqN2PSYEQs
%20(1).png)
CapMate provides the user with the unique ability to not only detect variety of caption/subtitle issues, but the first solution to provides an intuitive interface to review the result as well as automatically or manually correct the issues and generate a new caption file.
Offering CapMate on the AWS Marketplace provides numerous benefits to the users, including:
.png)
Venera Technologies, a leading provider of cutting-edge file-based media QC solutions, is proud to unveil a groundbreaking enhancement to its CapMate® caption and subtitle verification solution. Leveraging the power of Artificial Intelligence (AI) and Machine Learning (ML), Venera introduces the innovative Forced Narrative Detection and Correction feature, reinforcing its commitment to advancing content quality control and compliance in the media industry.
Forced Narrative is a term prevalent in closed captions and subtitles. Frequently TV shows or movies may contain segments where the spoken dialog is in a different language from the dominant language of the show. In such segments, it is often required for the narrative to be present in form of subtitle text in the main language of the show, in order to aid comprehension for viewers (hence ‘forced narrative’). However, absence of such narratives can diminish the viewing experience, sometimes significantly. Therefore, a notable amount of human effort is needed to not only examine the entire content and look for absence of such ‘forced narratives’, but also to translate those segments into the dominant language of the content and add the ‘forced narrative’ text. This results in drastic inefficiencies in verification and subsequent addition of forced narrative.
The new Forced Narrative Detection feature in Venera’s CapMate solution addresses this challenge by employing sophisticated algorithms trained on extensive datasets. Through advanced linguistic analysis and contextual understanding, CapMate’s AI model identifies segments where the dialog is in a different language, and if it detects missing subtitle text, it translates the dialog to the dominant language and generates the necessary forced narrative text. CapMate performs this with accuracy, enabling content creators, broadcasters, and streaming platforms to ensure the integrity and accuracy of their captions and subtitles.
“We are excited to introduce the Forced Narrative Detection feature in our CapMate solution,” said Fereidoon Khosravi, Chief Business Development Officer at Venera Technologies. “As content consumption continues to diversify across platforms and devices, maintaining accurate and compliant captions and subtitles is essential. With this latest innovation, we empower our clients to deliver content that is accessible, engaging, and true to its original intent.”
Venera Technologies remains at the forefront of innovation in Audio, Video, and Caption QC solutions, continuously enhancing its offerings to meet the evolving needs of the industry. The addition of Forced Narrative Detection to CapMate further solidifies the company’s commitment to delivering cutting-edge tools that enhance caption/subtitle quality and ensure regulatory compliance.
For more information about the Forced Narrative feature in CapMate and other solutions offered by Venera Technologies, you may contact them at sales@veneratech.com, or visit www.veneratech.com to request a free trial. You can also go to Venera’s NAB 2024 page to arrange for a meeting at NAB 2024 show at Las Vegas Convention Center, West Hall, #W1858(April 14 – 17, Las Vegas, USA).
Venera Technologies provides cutting-edge file-based QC solutions to the digital media industry, tailored to the evolving requirements of its customer and the industry, offering innovative tools and technologies for content quality control, compliance, and delivery. Venera’s suite of QC solutions is used by some of the largest Media companies in the world, as well as a number of smaller boutique post houses and production companies.
Venera’s CapMate®, is the first comprehensive solution for verifying caption or subtitle side car files that can accurately and quickly detect (and correct) and report on complex issues such as caption sync, Standards compliance, and Forced Narrative.
With a focus on leveraging advanced AI and ML algorithms, Venera Technologies’ suite of QC solutions empowers media companies to optimize workflows and deliver high-quality content across diverse platforms.
.jpg)
Venera Technologies, a leading provider of cutting-edge file-based media QC solutions proudly announces the launch of its latest innovation: an advanced AI-powered Audio Profanity Detection feature integrated into its cloud native Quasar® Audio/Video QC solution. This groundbreaking addition showcases Venera’s commitment to enhancing content quality control and compliance in the media industry.
In today’s dynamic media landscape, ensuring that content meets regulatory standards and audience expectations is critical. Venera Technologies recognizes this need and has leveraged the power of Artificial Intelligence (AI) and Machine Learning (ML) technologies to develop a sophisticated solution for detecting audio profanity with unparalleled accuracy and efficiency.
The newly introduced feature in the
Quasar solution utilizes state-of-the-art algorithms trained on vast datasets
to analyze audio content in media files to accurately identify and flag
instances of profanity, including vulgar language and offensive terms, based on
user-defined set of words and phrases.
Key highlights of the Audio Profanity Detection feature include:-
· Customizable Vocabulary: Users have the flexibility to create a list of words and phrases that are considered profane for their audience and according to their local culture or regulatory standards, allowing for tailored and optimized profanity filtering.
· Scalability: Designed to meet the demands of large-scale media operations, Quasar’s Audio Profanity Detection feature is highly scalable, capable of processing vast volumes of audio content with efficiency and speed.
“We are thrilled to introduce the AI-powered Audio Profanity Detection feature in our Quasar solution,” said Fereidoon Khosravi, Chief Business Development Officer at Venera Technologies. “In today’s fast-paced media landscape, maintaining content integrity and compliance is crucial. With this latest addition, we empower broadcasters, streaming platforms, and content creators to uphold the highest standards of quality and decency in their audio content.”
Venera Technologies remains committed
to continuous innovation and advancement in Audio/Video/Caption QC solutions,
delivering cutting-edge tools that streamline workflows, enhance content
quality, and ensure regulatory compliance.
For more information about the Audio Profanity Detection feature and other solutions offered by Venera Technologies, you may contact them at sales@veneratech.com, or visit www.veneratech.com to request a free trial. You can also go to Venera’s NAB 2024 page to arrange for a meeting at NAB 2024 show at Las Vegas Convention Center, West Hall, #W1858(April 14 – 17, Las Vegas, USA).
About Venera
Technologies
Venera Technologies provides cutting-edge file-based QC solutions to the digital media industry, tailored to the evolving requirements of its customer and the industry, offering innovative tools and technologies for content quality control, compliance, and delivery. Venera’s suite of QC solutions is used by some of the largest Media companies in the world, as well as a number of smaller boutique post houses and production companies.
Venera’s Quasar® the first native cloud-based QC solution, was developed natively for the Cloud environment with features such as dynamic scalability and usage-based pricing model, along with advanced QC functionalities, such as Audio Profanity Detection.
With a focus on leveraging advanced AI and ML algorithms, Venera Technologies’ suite of QC solutions empowers media companies to optimize workflows and deliver high-quality content across diverse platforms.
Unleash the power of rich review & collaboration with QCtudio™,
the cloud-based platform designed to be the ultimate companion to Quasar.
Elevate your quality control efficiency like never before!
Review
Quasar's QC results with integrated audio-video playback directly on the player
timeline.
Directly add
review comments against various reported QC issues for collaboration.
Modify the
alert categories to mark them as “Creative Intent” or “False positives”.
Export
updated QC reports including the comments and revised alert categories.
Export the
alerts with their categories in formats compatible with NLE solutions, starting
with Davinci Resolve.
Streamline quality control with a user-friendly interface.
QR code or Quick Response code is a two-dimensional barcode invented in 1994 by a Japanese company Denso Wave for labelling automobile par...
%20(1).png)
