AI dubbing vs. traditional dubbing: when to use each localization method

Over the last half-decade, social and streaming platforms have proliferated in tandem with content demand. It’s unsurprising, then, that localizing for global audiences is high on content owners’ agendas, so much so that global translation service revenue is projected to reach USD$47 billion by 2031. Much of that valuation will be driven by traditional dubbing, but almost a third will be driven by AI dubbing, which automates the process for efficiency and scalability. Here, we look at the differences, similarities, and pitfalls of AI dubbing technology and traditional dubbing methods to guide you towards the best possible solution for your business model and content type. 

What is AI dubbing and how does it work?

Artificial intelligence dubbing, widely known as AI dubbing, replicates the traditional dubbing process by using machine learning to translate and produce synthetic voices to dub content. It uses large language models and natural language processing to translate the original material, and machine learning to create and apply lifelike AI voices to articulate the translated material to reflect the original material's delivery and intent. 

The highest quality AI dubbing begins with commissioned audio data specific to the use case (reality TV, films, lifestyle, etc.), which is then used to train custom machine learning models. Once trained, these models apply what they have learned to replicate the intricacies of human speech in the new language. 

AI technology dramatically reduces the turnaround times and cost of dubbing by automating the process and eliminating the need for multiple stakeholders. Arguably, its greatest contribution to the localization space is enabling content owners to dub content that wouldn’t ordinarily qualify for dubbing due to the prohibitive costs of the traditional method.

What is traditional dubbing, and how does it work?

In traditional dubbing, expert translators and writers adapt the original script into the new language/s. Casting directors then find voice actors who match the original delivery or, in the case of films with famous cast members, call on voice actors who always dub the voice of a well-known actor. A lot of planning and stakeholder management goes into the traditional dubbing method: everything from script preparation, scheduling and booking actors and recording rooms. Voice actors narrate the new script, timing their performance to match the actors’ lip movements. Their performance is recorded in a studio with a recording engineer.

With their ability to deliver a huge range of human emotions by varying pitch, pace and intonation, voice actors achieve high levels of expressivity that are difficult to replicate in totality with technology. They sometimes even work with dubbing directors who work through character development and line delivery to achieve the best possible performance and deliver a seamless experience to global audiences.

In the entertainment industry, traditional dubbing is often the go-to method for highly expressive content like movies and dramas featuring multiple characters and intersecting storylines because it produces high-grade dubs. However, the process requires multiple stakeholders, both on the content owner side and localization provider side, making it expensive and time-consuming.

When to use traditional dubbing and when to use AI dubbing

We’ve covered the pressures of high demand on traditional dubbing and its halo effect on the entertainment industry's ability to localize its content. We've also touched on the method's pitfalls, which are well-known in the industry—high costs, long turnaround times, and complex processes. While AI technology in dubbing solves these problems, it is not immune to criticism: it can scalably achieve human-level expressivity for many content types but cannot yet do so for all.

When considering which mode is best suited to what content type, it’s important to consider turnaround times and cost and their impact on content monetization. It's also important to consider the depth of human emotion delivered by the dubbing mode and how it corresponds to audiences’ regional and platform-specific (for example socials versus streaming) quality expectations and the scalability of the method.

Which is faster and more cost-effective: AI dubbing or traditional dubbing?

Harnessing artificial intelligence is a faster and more cost-effective solution for customers looking to dub large volumes of content in short timeframes. By using machine learning to automate the translation and dubbing process, AI dubbing streamlines the process to reduce turnaround times and costs.

The speed of automated dubbing has many advantages: it enables content owners to test out new markets and new localization strategies without investing outsized amounts upfront; this means that the payback period is shorter than traditional dubbing, and with a shorter time to market, content has longer to monetize.  

However, voice actors' ability to capture the emotional nuances of a character is second to none. When choosing a dubbing method, weigh the importance of conveying the same level of human emotion with the cost, time and scalability of the dubbing method.

Is AI dubbing more scalable than traditional dubbing? 

AI dubbing enables large volumes of content to be localized into many different languages. For content owners producing vast amounts of fast-paced content (news, social videos, snippets of longer-form content) whose budgets wouldn’t ordinarily stretch to dubbing this content via traditional methods, artificial intelligence in the dubbing sphere opens up new global distribution possibilities.  

Similarly, content owners no longer have to reduce costs by choosing just a handful of languages to dub into. Using AI dubbing tools, they can dub into multiple languages that are widely spoken but underserved by dubbing, increasing audience size and making content truly global.

Is traditional dubbing more expressive than AI dubbing?

With its vast cast and creative teams, traditional dubbing remains the go-to approach for producing the best-quality dubs for top-tier content involving many characters, both adults and children, in dramatic, complex storylines that portray complex emotions like sarcasm or disappointment. The aim is to give viewers a seamless experience; they aren’t watching a dub but a reversion in their language. The complexity of the process, however, means that it is not scalable to apply it to multiple languages; even studios like Netflix limit the languages they dub into using traditional methods. 

However, AI dubbing has a significant role to play in this process, in particular when it comes to reducing turnaround times. Speech-to-text (STT) technology and video recognition tools help with script creation and on-screen text localization. Speech-to-speech (STS)  technology can be harnessed for pick-ups, crowd and background utterances, and smaller secondary characters. AI summary tools are also great for creating show guides and character profiles. 

Other good use cases for AI dubbing in this genre are audio description (narration for the visually impaired), lectoring (when the original audio is lowered so the voiceover takes centre stage), a narration style commonly used in Eastern European content and some animated content. 

Is AI dubbing good quality?

While AI dubbing can be used to dub drama, most often to tackle secondary roles, it comes into its own in the unscripted space. In documentary-style programming and lifestyle shows, the emphasis is not on replacing the dialogue and lip-syncing to convince the audience that they are watching an original production but on accurately conveying the information and message. 

To remain authentic to documentary or unscripted content, the original interviews and footage remain but at a lower volume, so the localized language voice-over is prominent. The narration is usually replaced fully to help with audience engagement. Humans are still an integral part of this process: at Papercup, expert translators ensure translation accuracy, adapt it for local markets and finesse the performance of the synthetic voices. 

As AI voices become more expressive, AI dubbing is lending itself to a third tier: phrase syncing or dialogue replacement, servicing genres such as social media videos, reality TV and game shows where budgets are tight but much more emotive voices are needed for audience engagement.

AI dubbing can help reduce language barriers by making video content, that would ordinarily have remained locked in a single language, available in audiences' native languages.

Humans are integral to both traditional and AI dubbing

AI dubbing is widely considered a wholly automated service where videos can be uploaded and dubbed into a different language or languages instantly. In reality, humans are integral to creating a good quality dub. 

AI dubbing and traditional dubbing largely follow the same steps of script creation, translation, adaptation, casting, voicing and audio mixing. In AI dubbing, however, machine learning automates many of these processes and some are omitted comepletely like line counting to work out actors’ fees, preparing individual scripts, and booking multiple recording sessions, making the workflow more efficient.

At Papercup, we also have dedicated teams focusing on customer success. Our account and channel managers continuously work with customers to develop their dubbing strategy and optimize content performance on social media platforms. 

AI dubbing and traditional dubbing are complementary

AI dubbing does not replace the need for humans to do complex tasks and artistic work like script adaptation, making creative decisions and finessing the dubbing either within a tool or using speech-driven technology. It does, however, automate the process for content that would otherwise remain undubbed.

Some of the traditional human roles have certainly shifted; for example, script adapters can now listen to the dubbing output while creating scripts and changing the voices, which is impossible in traditional dubbing. Voice actors can earn extra income by licensing their likenesses in a safe and controlled environment to drive the creation of multiple voices using the latest speech-to-speech technology, all while continuing to work on genres where traditional dubbing is best. 

Considering their distinct benefits and downsides, we see traditional dubbing and AI dubbing as complementary modes that work together to meet the burgeoning demand for global content. 

Get in touch to discover how AI dubbing can streamline your dubbing process.