AI-Human Collaboration: Next-Gen Translation for Global Media Success

The growth in media content consumption is fueling the exponential growth of localization demands. Streaming services and FAST channels must compete globally, necessitating high-quality translations for original programming and archived content. However, the media and entertainment market is experiencing a critical and significant skilled translator shortage, which offers an opportunity to address this complex challenge with a mix of experienced professionals, technology, and training. The intersection of human expertise and AI for machine translation is helping us explore exciting hybrid collaboration possibilities of AI efficiency and human finesse. Rather than viewing it as an either/or situation, combining the strengths of both approaches offers us numerous successful case studies in enhanced translation quality while reducing manual and possibly tedious effort.

Whether AI works as an alarm programmed to to alert us of certain conditions, events or patterns, or as a tool serving to assist us in various tasks, or acts as an agent working autonomously, enhanced AI and human interaction is becoming more multi-modal. The rise of remote work environments and AI go hand in hand and this combination has the potential to create synergies; AI-powered collaboration tools can facilitate remote teamwork, AI can automate repetitive and time-consuming tasks, allowing remote workers to focus on more high-value activities. We also predict many job transitions from manual and administrative to strategic and creative - essentially making AI work for you.

For example, in a typical localization process (for a 2-hour movie) that includes selecting the right tools and skilled professionals, a couple of rounds of quality control, revision, and distribution, a collaborative human/AI model will streamline the process and save up to 30% of the time and cost for language service providers. To further enhance progress, XL8 leverages a Language Service Provider’s (LSP) data to create a continuous feedback loop for its self-improving model, teaching our engines to constantly learn. The time spent on manual quality control will be reduced as our AI model gets even smarter.

A Complete AI Package for Media Localization

Generative AI in the media and entertainment industry transforms how content is produced, distributed, experienced, and monetized. However, many current AI technologies and services cannot solve the challenges of low-quality training data, which often uses scraped web pages, or documents and data that are unsuitable for M&E. Many services also exist as individual silos of transcription, translation, and dubbing tools, creating a fragmented experience for language service providers.

Considering all these challenges, XL8 has built strong partnerships with LSPs, using 100% curated data perfected by linguists, equating to exceptionally high-quality localization services. We’re focused on the colloquial and contextual data specific to the media and entertainment industry and utilize Multimodal Large Language Models (MLLMs) to combine the capabilities of natural language processing (NLP) with other AI modalities, including automatic speech recognition (ASR), machine translation (MT), and text-to-speech synthesis (TTS). Connecting this overarching technology in a seamless and intuitive interface to unify tasks across an entire project reshapes the way LSPs work.

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Generative AI in Action - Pushing the Boundaries

Content localization and other post-production tasks (e.g., metadata generation, trailer creation) have become more efficient with the help of AI, which stems largely from its capacity to accelerate processes. For example, generative AI can be immensely helpful in crafting content related to videos. Whether generating video descriptions, scripts, captions, or summaries, generative AI can streamline writing by providing engaging text. Additionally, it can assist in creating metadata for videos. Video Generation algorithms are also a model of efficiency as they analyze the original footage, detect mouth movements, and synchronize the dubbed audio with the lip movements of the characters on screen.

At XL8, customers are taking advantage of our auto-generated translation glossary feature, which establishes a common set of terms and definitions, reducing ambiguity and misunderstandings - essentially allowing the team to speak the same language linguistically and contextually. This is especially useful when team members don’t have prior knowledge of the topic and can be integrated into crucial aspects of the localization workflow. Our AI synopsis writer feature uses natural language processing (NLP) techniques to automatically generate concise summaries of media content. This saves time by quickly summarizing large volumes of content and is especially useful for large libraries of movies and other archived content.

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Opportunities for AI-Driven Real-Time Interpretation

We ask ourselves whether the market is ready for real-time AI-supported interpretation and translation without human post-editing. The goal is to bridge the gap between produced AI quality and expected AI quality, and we know that the expected AI quality sets the standard for its performance.

With an incoming younger generation’s familiarity with AI, along with a labor shortage in our industry, we’re seeing quality requirements and expectations evolve. Advances in deep learning architectures and data preparation continue to increase the quality delivered by AI and steadily improve over time. Whether improvements can be attributed to advancements in AI algorithms, increased availability of training data, and ongoing research in the field, it’s apparent that real-time AI interpretation is successful in numerous applications, including short-form videos, live events, educational content, and FAST channel content.

This shift reflects a growing confidence in AI's capabilities to deliver reliable results in other domains such as VODs, promotional videos, and broadcasting – just to name a few. Real-time interpretation and translation demand a delicate balance between speed and accuracy.

Speech-to-Text (STT) systems convert speech to text, which can be translated in real time and provide quick processing without compromising accuracy. In what is typically a post-production editing part of the media chain, interpretation and translation using XL8’s EventCAT (using advanced AI, STT, MT) is now instant with zero post-edits.

Imagine real-time interpretation for broadcast subtitles – and imagine how that seamlessly bridges language barriers and enhances communication across audiences in multi-lingual meetings and digital or in-person summits, events, and broadcasts.

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Remote Content Production

AI-enabled productivity tools for remote teams are transforming remote setups in the media and entertainment industry, helping drive engagement, streamline operations, improve content quality, and reduce costs. Whether it’s seamless collaboration and file sharing among editors, sound engineers, and visual effects artists, remote casting/auditions, remote production management, or AI-driven production tools, remote content production is being embraced worldwide. As a technology partner to many global media organizations, XL8 solutions are being leveraged for its remote production capabilities.

One example is the recent Asian Television Awards (AKA) -  Asia Emmy Awards, an annual event celebrating excellence in television programming and production across Asia. Using the XL8 technology for AI interpretation and translation into 7 different languages for 9 countries, remote producers enhanced viewer engagement, expanded audience reach, and provided a more personalized and immersive viewing experience for audiences across Asia and beyond. This hybrid human + AI approach offers an interesting solution for achieving accurate, reliable, and culturally appropriate translations - at scale.

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Looking Forward - Remote AI-Based Video Production Studios

Video platforms that harness AI's power will transform how live webinars, interactive events, broadcasts, and movies are produced. Imagine the entire video production process available as a single-person (director/producer) software seat. With new AI models on the horizon, such as Sora, where users can create realistic video scenes from text instruction, there’s a potential opportunity for a single-person producer platform to create various video content, including movies, trailers, and short-form videos. Conceptually, this type of AI-driven platform would support pre-production concept development, scriptwriting, storyboarding and visualization, audio generation with voices, sound effects, background noises, audio mixing, and video production for generating final scenes, all the way to publication, distribution, marketing, and monetization. This type of solution has the potential to empower solo filmmakers to bring their creative visions to life more effectively, fostering greater diversity and innovation in storytelling.

Harnessing the power of AI has the ability to break down language barriers and foster more global understanding. It’s playing a transformative role in the global exchange of ideas and creating communicative opportunities for everyone—in every country worldwide.