Machine translation and linguistic AI for asset management – enabling transformation

Valeria Cannavina 12 Jul 2023 6 mins
Adaptable mt language weaver rws
In our last blog, 'Machine translation and linguistic AI for asset management – a question of trust,' we discussed the specific challenges of delivering compliant asset management content at speed and at scale. We also touched on how RWS machine translation (MT) and linguistic AI solutions can provide answers to these complexities through a transformative approach to automating the translation of content.
 
But how do we deliver linguistic innovation? We have placed the five pillars below at the heart of our transformational linguistic AI strategy.
 
  • Language suitability: not all languages are equally suitable for MT. Deciding factors are the language itself, the volume and the validity of the training data used to build the language model and the availability of linguists specializing in asset management content. It is generally good practice to focus a new and evolving MT strategy on high-traffic languages suitable for a post-editing solution and, at the same time, create a roadmap for future adoption. This should consider any expansion plans, emerging markets and the potential need to develop specialist linguistic resources.
  • Content suitability: all content is potentially suitable for some level of machine translation.  By proactively defining the business outcome that is the desired end goal, we can optimally assess content suitability and associated factors. These include linguistic assets, such as style and terminology, and process-specific technical considerations, such as length restrictions. Assessing content also creates a map to pair each content type with the right service and technology.
  • Subject matter experts: we believe in humans and technology working hand in hand. Our in-house experts combine years of expertise in their respective fields, from linguists to developers and consultants. Our expert-in-the-loop approach ensures an optimum use of automation while minimising compliance risk through the use of skilled human translators with industry terminology expertise.
  • Technology: Language Weaver builds enterprise-grade MT solutions for global businesses. Working directly with your MT provider offers significant value when creating, customizing or improving MT models.
  • Scalability: a successful MT and linguistic AI deployment relies on scalability to adapt to the fast-changing needs of asset management firms. A comprehensive technology and service offering is the best approach to solve the combination of fast turnaround times, changing regulations, and high quality expectations.
 
MT and linguistic AI can potentially revolutionize how asset management firms approach localization. As linguistic AI evolves and advances, asset management firms can harness its potential to gain a competitive edge, drive innovation and unlock new opportunities. 
 
Valeria Cannavina
Author

Valeria Cannavina

Linguistic AI Consultant
Valeria Cannavina has 13 years of experience in project management, process improvement and workflow innovation. She joined SDL (now RWS) in 2014 as a senior project manager, moving to the RWS Linguistic AI team in early 2020.
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