Asia-Pacific Broadcasting (APB) March 2018 Volume 35, Issue 2 | Page 12

PANELLISTS
❝ In terms of ensuring quality , we ’ ll see machine learning become increasingly integral in improving the accuracy of captioning over time .❞
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April March 2012 2018
NewTek software-defined hardware devices offer more options
NewTek has announced new features for its Connect Spark converters and NDI pantilt-zoom ( PTZ ) camera . The latest version of Connect Spark includes multi-camera virtual PTZ capability , multicast support , ability to connect across networks , LTC time code support , as well as improved audio . NewTek ’ s NDI PTZ camera , said to be the “ world ’ s first ” PTZ camera able to deliver video , audio , tally , PTZ control and power over a single Ethernet cable , is now updated with multicast support and “ vastly enhanced ” picture quality , NewTek informed .
Core SWX unveils Nano-M battery
Exclusively designed for Panasonic cameras , Core SWX ’ s new cine battery , the Nano- VBR98 , is a 7.4V battery pack with a 12V power tap ( 2A max load ). It has a capacity of 98Wh and weighs 0.9 pounds ( 0.4kg ), and is equipped with a four-stage LED power gauge and a power tap . The Nano-VBR98 is also the first battery pack to offer Core ’ s patent-pending SmartTap protocol , which will allow future integration with devices to utilise the smart battery data in the pack .
Next Month @ Creation
4K / Ultra HD Acquisition

PANELLISTS

Dr Ahmad Zaki Mohd Salleh
Group GM , Engineering Media Prima
Phan Tien Dung
CTO Vietnam Digital Television
Mike Whittaker
Executive Vice-President and CTO , Asia-Pacific and the Middle East , Fox Networks Group Asia

Content that speaks multiple languages

Key advancements in subtitling and closed captioning , including AI and machine learning , are enabling content owners to bring their content to global audiences . Shawn Liew reports .

For broadcasters and media companies delivering content globally on a multitude of platforms , subtitling and closed captioning remains one of the most important , and challenging , broadcast functions to execute .

Delivering closed captioning at scale is costly and the manual undertaking can be burdensome to production teams , David Kulczar , senior product manager , Watson Video Analytics , IBM Watson Media , points out .
Another major challenge with closed captioning , he tells APB , comes from a language and compliance standpoint . “ Language is nuanced in a way that is sometimes difficult to capture and deliver in an automated caption . Programmes require context , and this is where machine learning can be incredibly valuable in increasing precision over time .”
Kulczar cites the example of the 2017 Tennis US Open , where IBM Watson Media powered closed captioning of the event , and was able to navigate nuanced tennis lingo . “ With a power artificial intelligence ( AI ) and machine learning combo , Watson differentiated between ‘ love ’ the emotion , and ‘ love ’ within the context of tennis .”
Compliance , he adds , is another area that is “ tricky ” to navigate globally . “ Regulations surrounding captioning vary between industries , geographic locations and delivery methods , making it challenging to provide compliant captioning .”
With regards to compliance constraints , IBM ’ s offering is targeted as a tool to help companies reach compliance more efficiently — rather than as a tool that certifies compliance . Because of this , IBM ’ s products are not directly impacted by regional compliance regulations , although the company constantly reviews how its tools can better help customers adhere to compliance regardless of region .
Product features such as Smart Layout
Another area in which AI is transforming captioning is within live broadcasting .
❝ In terms of ensuring quality , we ’ ll see machine learning become increasingly integral in improving the accuracy of captioning over time .❞
— David Kulczar , Senior Product Manager , Watson Video Analytics ,
IBM Watson Media
IBM has launched Watson Captioning , a new standalone offering that leverages AI to automate the captioning process , while ensuring increased accuracy over time through its machine learning capabilities .
were created to help with many of the compliance differences across regions , and in a bid to further remove the frictions associated with these processes , IBM launched Watson Captioning last month . This is a new standalone offering that leverages AI to automate the captioning process while ensuring increased accuracy over time through its machine learning capabilities . “ By adding a layer of searchable , textual data to video libraries , Watson Captioning empowers media companies to more easily adapt generated captions to meet specific compliance standards ,” Kulczar highlights .
Besides Watson Captioning , IBM Cloud Video recently introduced the ability to convert video speech to text , an indication , perhaps , of a larger push towards automation in production processes for media and entertainment ? Agreeing , Kulczar suggests : “ AI and automation are powerful tools for saving time and expediting resource-intensive tasks within production workflows , and we ’ ll definitely see more investment in the area in the coming years .
“ In terms of ensuring quality , we ’ ll see machine learning become increasingly integral in improving the accuracy of captioning over time .”
Specifically with Watson Captioning , IBM wanted to ensure that the captioning experience was catered to media companies ’ needs . One of its standout features is a customisable glossary , which allows users to input a specific set of words and phrases that may be unique to their company or industry . “ With the glossary in place and machine learning backing the solution , our customers can generate precise captions from the get-go that become even more accurate over time ,” says Kulczar .
As far as bona fide game-changers in the broadcast , media and entertainment go , does AI possess the potential to trump all comers ? “ Until recently , generating closed captions was quite a manual undertaking , and a costly one at that ,” Kulczar says . “ Now that AI has streamlined the process , production teams are freed up to work the editorial aspects of the production process .”
Another area in which AI is transforming captioning , he believes , is within live broadcasting . “ With AI , broadcasters have the ability to generate closed captions in near real time , something that was previously a major pain point .”
This is important , Kulczar explains , because intelligent captioning helps broadcasters to streamline their own