This is part 2 of a 2 part series. In this part, we cover how Artificial Intelligence-based dubbing is a powerful form of localization. In part 1 of this 2 part series, we presented an overview of why content localization is important and the advantages of voice dubbing.
AI for dubbing-enhancing the workflow, turnaround time, and quality of dubbed films
Innovative dubbing solutions providers are adopting AI for dubbing, training, e-learning, and corporate videos. By leveraging cloud computing, they have simplified the concept of any time, anywhere dubbing and helped reduce the time to market. The advancements in AI technologies have further enabled the dubbing solution providers to improve the volume and dubbing quality.
One of the critical developments that power the increasing reliance on AI-based dubbing is the AI speech translation engine. It is behind the move by a leading film production house in India to dub Bollywood movies in 10 Indian and 5 global languages.
Furthermore, CD Projekt Red, the maker of the action-packed role-playing game Cyberpunk 2077, aims to add a deeper layer of immersion for players by using AI for voice localization of the dialogue into 18 languages.
Another development is in the form of the Automatic Face-to-Face Translation protocol. The protocol can sync the visual, so the voice style and lip movement match the dubbed language. It can automate the dubbing process at different levels with different trade-offs.
For instance, the protocol can dub a movie scene in a particular language into a different language without discrepancies in the lip movement. A novel visual module, LipGan, which can generate realistic talking faces from the translated audio, is also incorporated with The Automatic Face-to-Face Translation protocol. Consequently, the protocol can significantly improve the overall user experience for consuming and interacting with multimodal content across languages.
A critical development in AI is Neural Machine Translation (NMT). NMT can significantly enrich the video dubbing process without altering on-screen content. In NMT, different algorithms work together to enable machines to learn expressions, grammar, and linguistic rules and subsequently predict complex sentences. Furthermore, NMT can learn new languages. Given sufficient data on the different parameters that define a voice, and concepts such as intention, punctuation, delivery, and projection nuances such as pitch and intonation will become more refined in automatic video dubbing.
Advances in AI for voice localization are making localized films, TV shows, and media more life-like. A few years ago, it was impossible to imagine that automated dubbing would be anything but robot-like. Today, there is variation in voice delivery, and the AI-dubbed versions are much more life-like. Besides, the process is faster and would have lesser errors than the traditional methods. Significantly, for the production houses, television broadcasters, and distribution companies, AI-based dubbing can help them air the dubbed versions simultaneously with the original version.
Through localization, content creators can reach audiences worldwide, providing content in their local language. Automating dubbing workflows speeds up this process immensely while also introducing increased accuracy. When AI technologies are added to the voice dubbing workflow, it can help complete the process quickly with minimum manual intervention and reduced costs. It’s a win-win situation for content creators and viewers. Shortened timeframe and decreasing costs are two critical areas where AI for dubbing has helped the creators, video production houses, and e-learning providers. For the viewers, AI’s deployment for video dubbing provides them with a high-quality viewing experience in their native language.