How Machine Translation Makes Localization Easy on Frazier

In addition to audio description, VIDEO TO VOICE is actively involved in other fields surrounding accessibility for digital media. To break down language barriers, Frazier includes a neural machine translation service. With lower costs and fewer delays, this option is a popular choice for clients wanting to create video content in multiple languages.

Jokes about online translation tools are so last decade. When the first real-time machine translation services emerged in the early 2000s, they were ridiculed for producing questionable results. At best amusing, and at worst wildly offensive, translations created this way would often be too literal and stray away from the intended meaning of the original text. 

But as technology has improved in recent years, there have been noticeably fewer “translation fail” memes doing the rounds on social media. The latest developments in machine translation involve neural networks. These are subsets of machine learning that try to mimic how the human brain works during the translation process.

Intrigued? Read on to find out everything you need to know about the language service industry, where providers are having trouble, and how machine translation makes localization easy.

It's simple – we all want access to content and information that is naturally communicated in our own language.

From a business standpoint, effective communication helps companies improve their brand image, boost customer satisfaction, and increase productivity of staff.

As well as keeping existing customers happy, translated content can help companies expand into other markets. This is backed up by findings in the 2020 Common Sense Advisory Report “Can't Read, Won't Buy”:

Weiterlesen

In addition to providing technological solutions for audio description, VIDEO TO VOICE is actively involved in other fields surrounding accessibility for digital media. For some time, VIDEO TO VOICE has been working in close partnership with the Fraunhofer Institute for Integrated Circuits (IIS) on topics such as automated mixing and MPEG-H Audio. The following article provides detailed analysis of the tools that make up MPEG-H Audio, a technology developed by Fraunhofer IIS to improve accessibility and deliver the best sound experience possible.

This is the second part of our series exploring the object-based approach to audio production and Fraunhofer IIS's involvement in developing MPEG-H Audio system. Part one focused on the fundamentals in traditional channel-based audio, the accessibility problems this approach causes, and the solutions that object-based audio can provide. 

With the basics covered, it's now time to take a closer look at the ground-breaking technology behind MPEG-H Audio and the various tools content creators can take advantage of. Let's start with the MPEG-H Authoring Suite...

Authoring in this sense is the step where metadata is created to enable playback devices to deliver on the three key principles of interactivity, immersive sound, and universal delivery.

Metadata is information that describes an audio object's existence, position, and function.

The MPEG-H Authoring Suite (MAS) is the place where content creators can create metadata, such as setting up presets, enabling interactivity options for viewers, and defining positions and properties of audio objects.

On the MAS, content creators can also monitor how their mix will be rendered in different layouts and make any necessary changes.

Weiterlesen

Dialog+: The Game Changer for Easier-to-Follow TV Dialogue

In addition to providing technological solutions for audio description, VIDEO TO VOICE is actively involved in other fields surrounding accessibility for digital media. For some time, VIDEO TO VOICE has been working in close partnership with the Fraunhofer Institute for Integrated Circuits (IIS) on topics such as automated mixing and MPEG-H Audio. The following article provides a fascinating glimpse at Dialog+, a production technology developed by Fraunhofer IIS to make TV dialogue easier to understand.

It's a frustration many of us have experienced while watching TV: We can't quite hear what the actor is mumbling during an important scene, so lose track of the plot for the rest of the show. Likewise, when the music, sound effects or background noises are too loud, the dialogue becomes difficult to follow, prompting us to turn up the volume to an uncomfortable level or switch over.  

To combat this issue, the Fraunhofer Institute for Integrated Circuits (IIS) teamed up with public broadcasters in developing Dialog+ – an innovative AI-based solution for making TV dialogue easier to understand. In essence, Dialog+ provides viewers with an enhanced version of the dialogue which they can select as an alternative to the original audio mix.

In late 2020, German television networks Westdeutscher Rundfunk (WDR) and Bayerischer Rundfunk (BR) conducted viewer testing to see how Dialog+ would be received. But before we examine the results, let's take a closer look at why TV dialogue is difficult to follow in the first place.

Weiterlesen