The Future of Multilingual Media – Studying GenAI’s Impact

Limegreen Media
The Future of Multilingual Media

It is indisputable that generative artificial intelligence (GenAI) has a transformational effect, and businesses will likely adopt GenAI more quickly.

In the middle of this technological tsunami, the media has been making headlines predicting the end of different professions, including marketing, engineering, translation, and law. However, given that we are currently in the very early phases of the GenAI journey, comprehending the precise dynamics of how GenAI will impact various businesses and services is a complicated task.

A survey by Boston Consulting Group (BCG) with 200 Chief Marketing Officers (CMOs) in 8 countries revealed that around 70% of respondents said their firms already use GenAI, while another 19% said they are testing it.
BCG

Being a prominent language services provider (LSP), Lime Green Media (LGM) has been researching the possible effects of AI on multilingual media.

We believe talking about the forces at work is a reasonable method to provide clarity and aid in navigating the impending changes. Therefore, this guide will discuss GenAI, how it works, the localization market at present, and GenAI’s impact on it.

So, let’s start with the discussion!

What Is Generative AI?

Deep-learning models that can produce high-quality content, such as text, images, and other media, based on the data they were trained on are referred to as GenAI. It includes algorithms such as ChatGPT and falls under the broad category of machine learning (ML).

How Does Generative AI Work?

It works by using an ML model to learn relationships and patterns in a dataset of human-developed content. Based on the learned patterns, it then generates new content.

The most common way to train it is to utilize supervised learning. It involves giving a set of human-developed content with its corresponding labels. GenAI then generates content similar to human-created content and labels it accordingly.

  • Improved Content Quality – AI models can learn from vast amounts of data and spot patterns that humans would miss. Therefore, the content produced by AI can sometimes be of a higher quality than human-produced content. As a result, we believe GenAI will generate more precise content that can be used for educational purposes.
  • Automated Content Generation – AI-powered language and image models can automatically produce content like social media posts, articles, and blog posts, saving time for experts and businesses who create content frequently.
49% of CMOs believe GenAI helps marketing organizations create content faster, with higher quality and greater variety.
BCG
  • Enhanced Content Diversity – AI models can produce text, image, and video material, among other types of content. This can assist companies and experts in producing a variety of captivating content that engages a larger audience.
  • Personalization – AI models can produce content tailored to each user’s tastes. This can assist companies and professionals in producing content more likely to be read or shared by their target audience.
A survey revealed that 91% of consumers express a greater willingness to do business with brands that recall their preferences to deliver relevant suggestions and offers.

The Localization Industry At A Glance

92% of all internet users, or almost 3.5 billion people globally, viewed an average of 17 hours of online video content each week. And when it comes to podcasts, around 464.7 million people across the globe tune into more than 5 million streams. Additionally, industry experts forecasted that by 2025, e-learning revenues will triple.

That being said, the need for multilingual multimedia content is growing along with the worldwide audience.

Video and audio localization, script translation and transcription, on-screen text and subtitling, voice-over, and dubbing are all included in multimedia localization. Since multimedia comprises text, images, movies, animation, and audio, translating it is difficult.

Here’s where GenAI comes into play, offering smooth multilingual content generation and translation. Given the quick development of GenAI, Gartner projects that by 2025, 10% of all data produced will be by AI, which is less than 1% today.

How GenAI Is Revolutionizing Localization and Translation

Now that you have an understanding of GenAI and where the localization industry is heading. It is time to take you a step further by discussing the impact of GenAI on localization and translation.

So, without further ado, let’s get started!

Subtitling and Captioning

The use of language technologies such as automatic speech recognition (ASR) and machine translation (MT) has greatly improved the subtitling and captioning processes.

ASR helps convert human speech from audio and video files into written text. Contrarily, MT utilizes AI to automatically translate text from the source language to the target language without human intervention. The workflow involves two steps – the multimedia content is first transcribed and then translated.

Nowadays, subtitling and captioning have become highly automated with the help of large language models (LLMs) and GenAI. These AI-driven tools can transcribe spoken words, translate them into multiple languages, and synchronize them with the video flawlessly. This saves time and guarantees accuracy and consistency across different languages.

A survey found that 50% of people from the US watch content with subtitles, 55% say it is hard to hear dialogues in movies and shows, 62% say they use subtitles more on streaming services than regular TV channels, and 57% watch content in public.

LLMs come with several benefits, including the ability to consider the surrounding text to produce MT results that are more in-context and contextually appropriate. Additionally, LLMs can utilize accompanying visuals through multimodal models to determine the most relevant target text. This feature further enhances the accuracy and consistency of the translation process.

Subtitling and captioning methods help in adapting multimedia content to a global audience, as they are more efficient and less expensive than dubbing.

The emergence of AI-powered technologies has opened up new possibilities for production houses to produce multilingual content easily and effectively.

AI-Assisted Synthetic Video

Apart from subtitles, voice-over and audio localization are crucial aspects of content creation, and GenAI is all set to bring a revolution. With the help of AI models, it is possible to replicate human voices accurately. This allows media, marketing, and e-learning organizations to provide content in various languages using the same video, eliminating the need for human voice actors.

The global AI voice generator market was valued at US $1.21 billion in 2022 and predicted to reach US $4.889 billion in 2032, growing at a CAGR of 15.40% during the forecasted period.

Modern AI-assisted synthetic audio uses advanced neural networks trained on extensive human speech, ensuring that robotic and monotonous voices are a thing of the past.

AI-generated audio provides a platform with a wide range of multilingual voices that can adjust to feedback. Moreover, it often matches studio-quality recordings and achieves high sample rates.

Certain AI audio technologies allow for seamless interaction with people from diverse linguistic backgrounds by enabling real-time translation during live sessions.

But What About the Challenges Associated with GenAI?

Some projects may require a level of domain-specific knowledge and cultural nuances that generative AI may not be able to provide. In such cases, human linguists with their deep understanding of cultural norms, can ensure that the localized content is culturally sensitive and resonates with the intended audience.

Security Concerns and Data Privacy

Most localization projects involve sensitive data that media houses hesitate to share or feed to AI due to potential security and privacy concerns. On the other hand, human translators can ensure a higher level of confidentiality and protection.

AI systems can be exploited to gain unauthorized access to private and sensitive information.
CIO

A Complementary Solution with Human Expertise

Localization requires gauging cultural nuances, linguistic context, and emotions of your target audience, which AI currently can’t understand or resonate completely. Thus, it is evident that businesses can use AI to scale and enhance but not replace human expertise.

Therefore, it is recommended that you use human-AI collaboration for maximum productivity and efficiency.

Generative AI’s success depends on “humanity in the loop”.

Bottom Line

Localization professionals can benefit from utilizing generative AI tools such as LLM and automation. These tools can assist in streamlining workflows, allowing professionals to focus on strategic tasks. Additionally, they can effectively address complex syntax, ensure brand voice consistency, maintain high content quality, and customize content for specific target markets.

GenAI can enable faster turnaround times, better outcomes, and reduced human effort in various languages, industries, and contexts. Therefore, it is crucial to embrace this innovative technology and continuously learn, adapt, and experiment with it to shape the future of localization.

Thus, to remain competitive, businesses must stay updated with the latest advancements, incorporate emerging technologies into their operations, and adjust their approaches accordingly. By doing this, they can foster innovation, delivering products and services that truly connect with various audiences globally, and ultimately drive the growth and prosperity of their companies.

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