Leveraging AI Technologies for Enhanced Multimedia Localization (2024)

Abstract: As demand for multilingual video content rises, multimedia localization is becoming crucial for Language Service Providers (LSPs), offering revenue growth and new business opportunities. To cope with labor-intensive multimedia workflows and the rise in client demand for cheaper and faster multimedia localization services, LSPs are starting to leverage advanced AI applications to streamline the localization process. However, workflows and tools adopted by media service providers may not be suitable for LSPs, while the plethora of available solutions makes it hard for LSPs to choose the ones that most effectively optimize their workflows. In this presentation, we assess AI technologies that offer efficiency and cost reduction in the traditionally human-driven workflows of transcription, translation, voice-over (VO), and subtitling with the goal to provide recommendations for LSPs on how to evaluate which tools work best for their processes.

## introduction with the growing demand for multilingual video content as a tool for companies to enhance their global communication and engagement, multimedia localization is becoming an important growth vector for language service providers (lsps), presenting opportunities to boost revenues and expand to new business cases @xcite . there are clear challenges faced by lsps in multimedia localization currently; the most significant are lengthy timelines, high execution costs, as well as difficulty sourcing and managing voice talent and video engineering resources. to cope with labor-intensive multimedia workflows and the rise in client demand for cheaper and faster multimedia localization services, lsps are starting to leverage advanced ai applications to streamline the localization process. however, lsps are often not prepared to adopt workflows and tools used by media service providers, while choosing tools that most effectively optimize their workflows is challenging due to the plethora of available solutions. in this presentation, we assess ai solutions that offer efficiency and cost reduction in the traditionally human-driven workflows of transcription, translation, voice-over (vo), and subtitling with the goal of guiding lsps in selecting the tools that work best for their processes. we investigate three categories of ai solutions for video localization workflows: open-source tools, commercial ai services and apis, and dedicated video localisation platforms. our evaluation examines tools for automatic transcription, machine translation, synthetic voices, and automatic subtitling in two high-demand language pairs: english to chinese (simplified) and english to spanish (latin american). we assess the tools based on criteria such as ease of use, cost, language availability and quality. our analy-sis suggests that out-of-the-box solutions that offer easy integration into existing workflows are a good transition step towards adopting ai, especially for low/medium project volumes. the existence of an in-house development team and higher volumes may justify investing in tailored solutions. still, the availability of languages is the most decisive factor in tool selection. we also show preliminary productivity gains when ai tools are applied in existing manual workflows. we conclude with recommendations for lsps in selecting ai tools based on key aspects like price, volume of multimedia projects, language pairs and the existence or not of an internal development team. ## preliminary productivity evaluation to evaluate productivity gains of using ai in the multimedia localization process, we conducted a series of real-life scenario tests using various ai tools. our initial test, covered in this paper, involved subtitling and voice-over of an 11-minute video with two speakers (male, female), replacing specific steps in traditional workflows with ai tools without the integration of workflow automation. the primary goal was to assess the productivity impact of low-level ai integration for lsps beginning their ai adoption journey. ## recommendations for lsps regarding ai tool selection when deciding which ai tools to integrate into their workflows, lsps should follow a systematic approach that takes into account the following aspects of their own production workflows: the volume of multimedia projects per year, the availability of a research and implementation budget, whether there is time to test different solutions beforehand, the main language pairs, whether there are engineers in the team who can work with open source solutions and, finally, whether the linguists assigned to multimedia projects are familiar with the tools or whether they need to be trained. our exploration of ai solutions for multimedia projects revealed that commercial ai services, which offer an all-in-one solution by the same provider and require medium technical skills, can be a good starting point in integrating ai and more suitable for low/medium project volumes. for high volumes, open source tools such as whisper can prove a worthy investment, but require staff with technical skills, as well as equipment with some computational power. tailored solutions also suit higher volumes. multimedia platforms, such as matesub for subtitling and speechify for voice-over, offer high quality and low management effort, but the cost is slightly higher and linguists need to be trained in using the tools. when selecting ai tools, lsps should not only consider the factors previously mentioned but also assess whether their multimedia projects are suitable for ai integration. the efficiency gains from using ai in multimedia projects can be significantly influenced by the complexity of the source material. for example, videos featuring multiple speakers, extensive on-screen text, or embedded pow-erpoint presentations present synchronization challenges when processed with ai tools. furthermore, the target audience of these videos must be taken into account, especially in vo projects. despite considerable advancements in synthetic voice technology, ai-generated voices remain distinguishable from human voices. lsps must carefully evaluate how the intended audience might react to synthetic voices when considering ai's role in their projects. ## conclusion the integration of ai technologies into traditional multimedia localization workflows offers significant advantages in terms of efficiency and cost reduction, all while maintaining high-quality standards. lsps can harness these tools to optimize their processes and effectively meet growing client demands. however, it is important to consider the initial effort required to incorporate ai solutions into existing workflows. depending on the chosen tools, this integration may demand varying levels of resource training, technical support, and budget allocation before realizing the anticipated time and cost savings. ongoing research should explore a broader spectrum of ai tools and refine evaluation criteria to support comprehensive tool selection strategies for lsps. we hope this presentation equips lsps to navigate the evolving landscape of multimedia localization, enabling them to meet client demands with efficiency and effectiveness, while upholding high-quality standards.