Automated Subtitling Solutions
Andovar’s AI-powered translation solutions are fully trained for television and media applications, providing you with accurate translated subtitles in hours rather than weeks.
Automated Subtitling Solutions
Andovar’s AI-powered translation solutions are fully trained for television and media applications, providing you with accurate translated subtitles in hours rather than weeks.
Broadcast Trained
MT engines
Process Automation
& workflows
AI Driven
technology
REST API
& connectors
Cloud-based
collaboration
Highly Secure encryption
technology
Putting Artificial Intelligence to Work for You
When you’ve got thousands of hours of content to localize, automation is the only answer. Andovar’s intelligent automated subtitle solutions ensure that you can go to market quickly with accurate, culturally aligned translations for all the shows you want to broadcast. Reach TV audiences around the world in record time — no matter how high your volume.
Automated Subtitle Solutions Designed for OTT Media
Media Studio offers a comprehensive set of enterprise-class tools for managing, creating, translating, editing, and processing subtitles, captions, and videos. Built on a foundation of high-quality subtitle-optimized machine translation engines, Media Studio has already delivered significant productivity and translation quality gains over hundreds of thousands of subtitles processed to companies all across the world.
Automated dialogue extraction
Automated dialogue transcription
Workflow automation
Translate More for Less
Media Studio features a suite of tools and technology with the sole purpose of making translators' lives easier. Media Studio's state-of-the-art Deep Neural Translation engines optimized specifically for subtitles helps deliver high-quality translations, typically with 50-90% of subtitle sentences either perfect or requiring minimal edits.
Rich HTML5 web-based editor
Subtitle-optimized machine translation
Terminology tools
Productivity gains
Technology that Works Overtime for You
However large your project, Andovar has the expertise – and the technology – to handle it efficiently. We will meet your high-volume and high-quality requirements on a global scale. Take your high-volume content to market in a matter of days and hit all your targets. Andovar’s intelligent, automated translation technology works overtime for you.
Comprehensive project management
Team collaboration tools
Asset management
Security
Challenges of Automated Subtitling
While machine translation has been used in localization for a long time, a few new challenges are present in subtitling projects:
Split sentences and missing end-of-sentence markers
For both humans and machines alike, not knowing when one sentence ends and the next sentence starts provides a challenge. Most subtitles lack end-of-sentence markers, and most have sentences that are split between frames; these issues need to be fixed before translation.
Custom rules
Stylistic requirements would normally be specified in a style guide for human translators, but they can also be applied through rules and machine learning for an automated process. As an example, profanity may be quite acceptable in the US market, but the vocabulary must be toned down considerably for a Thai-speaking audience by instructing the MT engine to soften any profanity found.
Changes in dialogue length after translation
Translation can result in shorter or longer text strings compared to the source language. Timing cues need to be adjusted in each frame, and sometimes frames must be inserted or deleted to accommodate these length changes.
Formatting of translated content
As the input to MT is complete sentences, the output from MT is also complete sentences. It must be reformatted into a subtitle format such as SRT or TTML.
Solutions for Automated Subtitling
In addition to the actual translation, there are several processes surrounding the creation and localization of subtitles that typically require significant human efforts. Many of these processes can be automated by Media Studio:
Extraction of dialog and metadata
Before a subtitle can be translated, a source language subtitle is usually made available. The layout and structure for each screenplay is wildly different, and even a human can take considerable time to extract dialog from the surrounding noise of video directives, mood indicators, general time stamps and other supporting information. Fortunately, these tasks can be automated – saving time and cost, and minimizing human error.
Extraction of text from audio-visual content
The second means of creating subtitles is using the audio-visual content as a source. This can be used with or without the dialog and metadata from the screenplay but is more accurate when the screenplay data is available. The accuracy of speech recognition, especially in videos where there is music, loud background noise or other factors, is not perfect, but accuracy has improved in recent years.
Adding or verifying timing information
The final challenge is the addition of timing information. Timing relates to when the actual text is spoken in a movie, as well as the timing of the frame changes. The time of the frame changes is important to understand; subtitles can be split across different frames, and if necessary can be adjusted and paraphrased to match the desired reading speed. Timing is adjusted by analyzing the audio-visual content, considering when people start and stop speaking as well as what scene changes and other country- and language-specific variables may be relevant.
Typically, creating original source-language subtitles for a 90-minute video as an SRT or TTML file with the correct timing cues can take between 36 and 48 hours. By combining the above approaches, the time needed can be reduced from days down to a few hours.