You’ve seen news along these lines: “AI dubbing, the future of localization”, “YouTube gets ahead in the localization race”, “AI dubbing never looked more natural”… The efforts to take audio localization a step beyond are bearing fruit, and AI Dubbing seems to be the next groundbreaking technology.
AI Dubbing is the automation of replacing an original audio in one language with a target language’s, synchronising lip movement, and matching the original’s tone and voice.
Thanks to technological advancements, the number of startups and AI dubbing providers is growing, and with that, the eagerness to acquire this technology for media localization. Here, we summarise some important discussion points on this growing trend.
The Rise of AI Dubbing
The global AI dubbing market is a relatively young one. With an estimated value of USD 794.3 million in 2023 and expectations to reach USD 2,918 million by 2032, AI dubbing is now one of the fastest-growing areas in AI.
Several factors are powering the AI dubbing growth:
- The explosion of media content thanks to influencers and social media use.
- Technological advances in NLP (Natural Language Processing), AI translation and voice synthesis technologies –among others.
- Demand for fast hyper-localization to keep up with trends.
Thanks to this, AI dubbing is making an entrance in the localization of e-learning courses, series, movies, social media, and video games. Not only are platforms like YouTube and Amazon Prime investing millions in enabling AI dubbing to reach and engage more audiences, but more startups and other tech giants are betting on developing their solutions. Nobody wants to lose this new race.
Source: Market.US
Key Developments
The current state of the art wouldn’t be possible without advancements in fields such as:
- Speech technologies: From speech-to-text, voice recognition, to speech-to-speech, and MT. These technologies are at the core of AI dubbing.
- AI models: Allow better and faster processing of information and streamline processes. New developments aim for Generalist AI models that can handle multilingual speech translation in a single framework.
Moreover, new releases boost advancements in the following areas:
- Realistic Lip-Sync and facial animation: This allows for matching speakers’ facial expressions and lip movement to translated content. The aim is natural-looking expressions.
- Voice cloning: Replicate the original speaker’s voice, pitch, and emotions. With these improvements, seamless AI dubbing for brand-consistent localization seems to be more attainable than ever.
Source: PERSO.ai
The Case of YouTube
YouTube’s rollout of AI dubbing for some of its creators was one of the most anticipated releases of the new year. Although technically launched in December 2024, during the first months of the year, the company has bet on the inclusion of more languages and more accessibility features.
We talked about how AI dubbing is making an incursion in movie dubbing, so this service is not completely new. However, YouTube’s implementation means that big players are now ready to join the competition, and other streaming and social media platforms will follow suit.
Although AI dubbing promises to help creators reach more audiences, viewers have already expressed their dislike over the “off-putting” results. Not to mention the cultural impact and technical hurdles. For instance, for videos with AI dubbed enabled, viewers see the dubbed version by default and have to go to settings to have the original version with subtitles if necessary. This impacts viewers’ experiences since a big number prefer the natural voice and feeling of original content. It hasn’t been long since YouTube rolled out these capabilities, so these concerns will probably be addressed soon.
Source: PPC Land
Other Players in the Arena
These companies are also playing a big role in pushing the industry forward:
- ElevenLabs: We mentioned this one before, and they keep aiming for voice cloning authenticity.
- Deepdub: Betting on Emotive Text to Speech (eTTS) technology that matches tone, intensity and “emotion” to provide live translation on sports commentary and live events.
- Dubformer: Also focused on tackling the “blandness” of AI AI-synthesised voices. Provides solutions for different media such as documentaries, news and TV shows.
Still Some Way to Go
Despite its many advantages, speed being the main consideration, some challenges must be tackled to take AI Dubbing to the next level:
- Quality control: This comes from AI translation in general. Addressing cultural nuances, idiomatic expressions, and emotional depth in AI-generated translations remains a challenge.
- Lip synchronisation: This results in an “off-putting” experience for viewers, especially in languages so different like romance and eastern languages.
- Natural and emotional speech: One of the biggest challenges for voice synthesis is emotional depth, speech patterns and sometimes, pronunciation. This turns out to be a major concern for hyper-localized content, where these issues matter the most.
- Ethical issues: Voice consent, copyright, transparent data practices, and the impact on traditional voice actors.
The Road Ahead
As a field in development, studios and companies are set on tackling current issues with the state of the art. Upcoming development will focus on:
- Increasing realism and emotional accuracy in AI voices.
- Broader adoption across industries, content types, and low-resource languages.
- Hybrid workflows combining AI efficiency with human creativity.
Source: KUDO
The forecasts were not wrong, and AI dubbing is on the rise. Innovations and collaboration across industries will most likely reveal a future where AI-dubbed content is more authentic and accessible. We can expect more adoption in different industries such as video game localization, but we’ll talk about that on our next issue!
