From media and entertainment services like Disney and video-sharing platforms like YouTube to music and podcast streamers like Spotify, multimedia content drives our digital experiences. The explosive growth of TikTok, which thrives on short-form video content, underscores our insatiable appetite for multimedia.

Global Multimedia Content in the Era of GenAI

Around 3.5 billion consumers worldwide, representing 92% of all internet users, watched an average of 17 hours of online video content weekly. Podcasts continue to grow in popularity, with 464.7 million listeners of over 5 million podcasts worldwide. And projected revenues from e-learning are projected to triple by 2025.

Yet, as the global audience grows, so does the need for multilingual multimedia content. Multimedia localization involves video and audio localization, script transcription and translation, subtitling and on-screen text, and voice-over and dubbing. Multimedia is more complex to translate, as it includes text, graphics, videos, animation, and audio.

This is where generative AI (GenAI) steps in, promising seamless multilingual content creation and translation. With the rapid rise of GenAI, Gartner estimates generative AI to account for 10% of all data produced by 2025, from less than 1% today.

How GenAI Could Impact Multilingual Multimedia Content Creation

Traditionally, translating multimedia content involved a source-to-target approach, where content created in one language was translated into others. For instance, an English video would be translated into French, Spanish, and other languages as needed. However, we are witnessing a paradigm shift with the advent of GenAI.

AI-powered tools like Microsoft Copilot are rapidly integrated into everyday workflows, automating multilingual content creation. Instead of the conventional source-to-target translation, we are moving toward a model where all language variants can be generated directly from the source. This means that a content creator could prompt an AI model to produce multimedia content in English, Chinese, and Arabic simultaneously, streamlining the localization process.

Google’s Gemini can also now connect to Google apps and services, supporting over 40 languages. And Spotify piloted its AI Voice Translation, which uses AI to translate podcasts into multiple languages using the podcaster’s voice.

How AI Will Change Multimedia

Subtitling and Captioning

Language technologies, including automatic speech recognition (ASR) and machine translation (MT), have significantly improved subtitling and captioning workflows. ASR processes human speech from video and audio files and converts it into text. MT uses AI to automatically translate text from one language to another without human involvement. The workflow follows a two-step process: multimedia content is transcribed and then translated.

However, large language models (LLMs) and GenAI can now automate this process efficiently. AI-driven subtitling and captioning tools can transcribe spoken words, translate them into multiple languages, and synchronize them with the video seamlessly. This not only saves time but also ensures accuracy and consistency across languages.

LLMs also have distinct advantages, such as considering the surrounding text for more in-context MT and contextually appropriate results. With multimodal models, LLMs can use accompanying visuals when deciding on the most relevant target text.

Subtitling and captioning are the most common ways to localize multimedia content, as they are faster and more cost-effective than dubbing.

Content types such as e-learning content often include videos and animations that require subtitles and captions to make them accessible to a global audience. The rise of these AI-enabled technologies is great news for e-learning organizations, enabling more ways to produce learning content in multiple languages.

AI-Assisted Synthetic Audio

In addition to subtitles, voice-over and audio localization are vital aspects of content. GenAI is poised to revolutionize this field as well. AI models can accurately mimic human voices, allowing media, marketing, and e-learning organizations to offer content in multiple languages using the same video without the need for human voice actors. Modern AI-assisted synthetic audio uses advanced neural networks, trained on extensive human speech. Gone are the days of monotone, robotic voices. AI-generated audio can deliver a platform of diverse, multilingual voices that can adapt to feedback. AI-generated audio now achieves high sample rates and often matches studio-quality recordings.

Some AI audio technology also enables real-time translation during live sessions, making it possible for to interact with participants from different linguistic backgrounds effortlessly.

The Road Ahead: GenAI and the Multilingual Future

The convergence of GenAI and multimedia content localization is reshaping how we create, translate, and deliver content to global audiences. As LLMs advance in their linguistic capabilities, the quality of translated content will improve significantly.

However, several challenges and considerations must be addressed as we embrace this transformative technology:

• Quality control. While AI-generated and translated content is improving, it is essential to maintain rigorous quality control. Human oversight remains crucial to ensure accuracy, cultural sensitivity, and context relevance in translations, especially in e-learning content where educational integrity is crucial.
• Bias and ethical concerns. Generative AI models learn from vast data sets, which may inadvertently perpetuate biases present in the data. Careful monitoring and ethical guidelines are necessary to prevent the propagation of bias, particularly in educational content.
• Training and adaptation. AI models need continuous training and adaptation to new languages and cultural nuances. Investing in ongoing development and refinement of AI models is essential to ensure they remain effective and relevant.

As such, there remains a need for human intervention. ASR and MT post-editors are crucial in reviewing and editing AI-translated content. There are also emerging roles, such as intralingual respeakers, ASR subtitling engineers, MT engineers for subtitling, subtitle post-editors, MT consultants for subtitling, and linguists to develop, train, and control ASR and speech-to-text technologies.

Use AI to Support Your Multilingual Content

Welocalize helps global brands maximize their investment in multimedia and e-learning to reach international audiences in 250+ languages through expert-led services. Our end-to-end multimedia localization and e-learning localization services, powered by AI technology and human language experts, include full-service video and audio localization, on-screen text or text-to-speech, transcribing, voice-overs, and subtitling.

Contact us to help you transform your multimedia content.