Slator - Language Industry News

On February 5, 2025, a team of researchers from Grenoble Alpes University and   Lingua Custodia , a France-based company specializing in   AI   and   natural language processing   (NLP) for the finance sector,   introduced   DOLFIN, a new test set designed to evaluate document-level   machine translation   (MT) in the   financial domain . The researchers say that the financial domain presents unique challenges for  MT  due to its reliance on precise terminology and strict formatting rules. They describe it as “an interesting use-case for MT” since key terms often shift meaning depending on context. For example, the French word couverture means blanket in a general setting but hedge in financial texts. Such nuances are difficult to capture without larger translation units. Despite strong research interest in document-level MT, specialized test sets remain scarce, the researchers note. Most datasets focus on general topics rather...

As 2024 comes to a close, it is time to reflect on the most popular stories, trends, innovations, and themes that made the Slator headlines throughout the year, highlighting key developments in the language industry. Here is a selection of stories that attracted the most attention and engagement from our readers around the world. Will Large Language Models Edge Linguists Out of the Language Industry? One of Slator’s  most-read stories in 2024  detailed a May 2024 paper from the  University of Zurich  and Georgetown University that explored the role of linguists in the evolving field of  machine translation  (MT). The entrance of  large language models  (LLMs) has reduced the reliance on linguists for grammar and semantic coherence while designing a system.  However, the authors concluded, there are a number of points in the process where linguistic expertise is still essential. These include building parallel corpora for MT; developing techno...

For the language industry , the year 2024 will go down as a year that had multiple developments and innovations at a fast pace, but this growth came with some distinct trends on the technological front that included translation feature as a service (TaaF), the emergence of multimodal AI , and retrieval augmented generation (RAG) and the use of large language models (LLM) enabled applications.  The integration of AI tools and human skill was in the central place in the deliberations of the industry specialists even as the different size companies had their perspectives. The responses of the readers and viewers as revealed in the weekly Slator polls are snapshots of the sentiments, preferences and scopes across the industry.  1. Is it Time for Language Service Providers to Change Their Mindset?  The language service sector has survived difficult times in the past but it was not business as usual for an industry that started 2024 on the wrong foot as reports of some firm...