There is no shortage of games on the market, and their production is becoming more accessible by the day. In this new normal, it’s difficult to get a leg up on the competition without using modern approaches. Below we present four current trends in Game Localization that can help you scale up the experience you provide.
QA Testing Technology:
Integrating quality assurance testing (QAT) with the best computer-assisted tools and localization technologies is highly beneficial for translators or QA analysts to review the performance profile of the translation. A novel QA tool is optical character recognition (OCR): an AI quality assurance testing tool that reviews written and printed texts from documents and images for anomalies. This helps reduce the functionality QA (FQA) burden typically incurred. Here you can read more about different approaches to QA testing or check out tools such as memoQ and Xbench.
Neural Machine Translation:
Machine translation was once no more than a novelty, but recent advances and investments in neural machine translation (NMT) have opened new possibilities. With the power of AI and refined algorithms, the filtered, self-honing approach of machine translation allows for accuracy and authenticity, which have traditionally been the fatal flaws in this method.
The output’s substantial quality is consequential to the source referential pool. For example, much of Google Translate’s infamous, often hilarious translations are due to its broad database. In video game localization, it’s vital to maintain an accurate and human-honed database to draw game terminology, vocabulary, and all linguistic congruencies from; both regarding quality and cost-efficiency. Gaming-specific, circular machine translation systems such as ModelWiz boost the game localization process without sacrificing quality. Such game localization tool adapts to game and product style, maximizing quality output based on over 10 years of gaming translation data.
Cloud Gaming and metaverse:
Gaming as a service, based on remote servers and directly streamed to the player's device, has become more popular as the technology has progressed. This can be better visualized by taking a sneak peek at the parts of the industry building Web 3.0 and the metaverse.
Skimming over its notoriety and even the subsequent transition of Facebook to Meta, the metaverse is a virtual space of 3D worlds conjured by the joining of virtual reality (VR), augmented reality (AR), and virtual spaces. It is being modeled not simply to accurately match our natural world through augmented and mixed reality experiences but to go beyond it.
It is an understatement to say that everyone’s reality is subjective to their own experience, but what that means is that intended immersion will be broken if the player can’t comprehend what’s going on. Whether in a traditional game platform or the metaverse, understanding is critical.
Renato Beninatto, the co-founder of Nimzdi (one of the biggest researchers into the relationship between language and buyer behavior) deems the role of language in-game immersion to be “as private and personal as it gets — and what is personal is what ultimately drives buying decisions”. Therefore, in-game features such as:
- Textual content: user interface, subtitles, captions, in-game text, etc.
- Audio content: dubbing and voice-overs.
- Creative marketing content: other graphics, advertising, etc.
- Cultural assets: referential imagery, storytelling, idioms, etc.
- Legal content: labels and policies.
Are mandatory to appeal to the market you’re tapping into.
Text to Speech (TTS):
Voice-overs can be as risky as relevance to get right. Their significance lies in the high quality of speech, language, placeholders, timing, cost, and hardship; each must be done very well. Errors must be minimal or nonexistent, and given the reputation of AI input mentioned previously, many would frown at implementing AI-powered text-to-speech in the game localization process. However, despite its infamy, labor, and price, automated text-to-speech can come in handy for cost reduction and QA as placeholders. Even when not at optimal quality, it can support decisions to adjust narrative, cinematics, and pace.
For example, it is common for localization to start in the later stages of game development. Multilingual voice-overs entail plenty of arduous but crucial arrangements for subtitles, frame time, and more. Consequently, AI-powered TTS can anticipate the required time and resources if utilized as a placeholder until the final script and in-game arrangements are defined. That way, it saves time and money by providing up-front hints as to how many adjustments will be necessary, where, and, when. This makes it far more likely that the actor’s final voice-over can be done once and done well.
This is a brief introduction to exploring current options in localization. Whether your approach is to focus on market expansion, cloud gaming, or incorporating more machine learning, you can start a free trial with us here.
Looking to set up game localization and ultimately use machine translation that makes sense for your game? Envisioning that your players can talk to each other in their native language while using the ModelWise™ API? Register here to get started on our free trial or contact us to discover how to build a scalable game localization workflow using the latest AI technologies.