EU Postpones Spain Language Decision Again

 

Almost two years after the first formal petition, Spain once again pushed for its three co-official languages, Catalan, Basque, and Galician, to be added as official languages within the European Union (EU). On May 27, 2025, the EU postponed any decision on the matter for a second time.

The first time the proposal was rejected was in September 2023, a little over a month after the Spanish Minister of Foreign Affairs, José Manuel Albares, requested for the Council of the European Union to include the languages. 

At the time, Spain presided over the EU government, which communicated that it had discussed the matter but needed more information, and deferred making a decision on whether to bring it to a vote.

This time, with Poland in the presidency, the EU has once again postponed any decision on the matter after at least ten countries, including Finland, Italy, and Germany, threatened to reject the proposal if it was brought to a vote. Sweden and other countries had opposed the 2023 proposal. Furthermore, a change in language policy at the EU requires a unanimous vote by all 27 EU State Members.

Initially, Albares proposed rolling out Catalan first and told Member States that Spain was willing to cover the costs of bringing all three languages into the EU (i.e., projected document translation costs).

A key piece of Spain’s Prime Minister Pedro Sánchez’s political campaign to remain in power was his commitment to the Junts Catalan party in 2023 to continue pressing the EU on co-official language inclusion in exchange for support at the polls.

According to the Spanish newspaper “El Diario,” Spain’s government spokesperson Pilar Alegría stated that Spain accepts the request to continue dialoguing and acknowledged that the proposal lacks enough support for the initiative to go forward.

What is a Language Solutions Integrator?

 

The term “Language Solutions Integrator” (LSI) was first introduced in the Slator 2025 Language Industry Market Report and is a term used to describe organizations whose core offering is to deliver fit-for-purpose multilingual content solutions by integrating language technology and AI with human experts as part of a fully managed solution.

While LSIs use technology — including AI — as part of the multilingual content production process to gain efficiency and reduce overall costs, they are ultimately responsible for the final outcome of multilingual content, as their value proposition includes the involvement of expert linguists and quality specialists.

These experts-in-the-loop (EITL) are typically deployed and managed directly by the LSI to ensure that outcomes meet the specific requirements of each buyer.

Examples of LSIs include TransPerfect, LanguageWire, RWS, Lilt, or Boostlingo — to name just a few among the thousands of LSIs operating globally.

A potential misconception is that LSIs do not own and operate any proprietary technology. However, this is not the case — LSIs monetize human-managed outcomes, even when AI-enabled. In fact, many LSIs own market-leading technology and may not even be tech-agnostic.

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Smartling, for example, is an AI-first company with an all-in-one language AI platform available to buyers of localization services and other LSIs. However, Smartling’s EITL services enable the company to deliver fully managed, fit-for-purpose multilingual content solutions, meaning that it is also a LSI.

In short, LSIs can work with any number of service providers and technology solutions with a core value proposition to deliver human-verified multilingual language content.

In addition, LSIs may choose to integrate or partner with Language Technology Platforms (LTPs), which are covered here.

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From a revenue perspective, LSIs typically operate on a project- or SLA-basis and price their solutions based on volume. LSIs that own proprietary technology may complement this with revenue generated based on a SaaS subscription model, whose primary metric is Annual Recurring Revenue (ARR).

IIT Bombay Explores Accent-Aware Speech Translation

 

In a May 4, 2025 paper, researchers at IIT Bombay introduced a new approach to speech-to-speech translation (S2ST) that not only translates speech into another language but also adapts the speaker’s accent.

This work aligns with growing industry interest in accent adaptation technologies. For example, Sanas, a California-based startup, has built a real-time AI accent modification tool that lets users change their accent without changing their voice. Similarly, Krisp offers AI Accent Conversion technology that neutralizes accents in real time, improving clarity in customer support and business settings.

While Sanas and Krisp focus on accent adaptation alone, the IIT Bombay researchers explore how accent and language translation can be combined in a single model.

“To establish effective communication, one must not only translate the language, but also adapt the accent,” the researchers noted. “Thus, our problem is to model an optimal model which can both translate and change the accent from a source speech to a target speech,” they added.

Scalable and Expressive Cross-Lingual Communication

To do this, they proposed a method based on diffusion models, a type of generative AI typically associated with image generation — DALL-E 2, which creates realistic images based on the user’s text input, is an example of diffusion models — but their applications extend to other domains, including audio generation.

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They implemented a three-step pipeline. First, an automatic speech recognition (ASR) system converts the input speech into text. Then, an AI translation model translates the text into the target language. Finally, a diffusion-based text-to-speech model generates speech in the target language with the target accent.

So, the core innovation lies in the third step, where the researchers used a diffusion model for speech synthesis. In this case, instead of creating images, the model generates mel-spectrograms (i.e., visual representations of sound) based on the translated text and target accent features, which are then turned into audio. For this, the researchers used GradTTS, a diffusion-based text-to-speech model, as the foundation of their system.

They tested their model on English and Hindi, evaluating its ability to generate speech that reflects both the correct translation and target accent. “Experimental results […] validate the effectiveness of our approach, highlighting its potential for scalable and expressive cross-lingual communication,” they said.

The researchers acknowledged several limitations, but they still see this as a promising starting point. “This work sets the stage for further exploration into unified, diffusion-based speech generation frameworks for real-world multilingual applications,” they concluded.

Authors: Abhishek Mishra, Ritesh Sur Chowdhury, Vartul Bahuguna, Isha Pandey, and Ganesh Ramakrishnan

AI Tech Consulting Firm Quansight Acquires Cobalt Speech and Language

On May 6, 2025, open source technology consulting firm Quansight announced that it had acquired Cobalt Speech and Language, a provider of automatic speech recognition (ASR), transcription, natural language understanding, and other voice technologies in multiple languages. The deal closed April 10, 2025. 

According to Quansight CEO Travis Oliphant, the purchase was for cash, earn-out, and equity in Quansight portfolio companies. 

“Quansight builds AI systems and has key developers who know how to build the tools behind AI (PyTorch, JAX, Tensorflow, and NumPy),” Oliphant told Slator. “Cobalt builds language systems that use these tools.”

Oliphant said that Quansight decided to acquire Cobalt, rather than build its own speech technologies in-house, based on the strength of Cobalt’s team, which could help maintain a certain speed of development. Of course, he acknowledged that the prospect of acquiring Cobalt’s customers was also attractive.

Massachusetts-based Cobalt was founded in 2014 by CEO Jeff Adams, known as the “father of Alexa” for his work on Amazon Echo. A press release on the acquisition quoted Adams as saying that Cobalt has “always focused on delivering highly customized speech and language tools that work in the real world, not just in the lab.”

Oliphant told Slator that Cobalt’s approximately 15 employees will join Quansight’s team of 80.

Cobalt currently offers several voice-enabled technologies, including Cobalt Transcribe for speech recognition and transcription. Its end-to-end speech recognition engines are powered by deep neural networks (DNNs), and clients can choose from two different DNN models based on their needs.

Hybrid models use separately tunable acoustic models, lexicons, and language models for maximum flexibility and customization for various use cases.

End-to-end models, meanwhile, directly convert sounds to words within the same DNN. This version works for general use and tends to produce more accurate transcriptions (based on word error rates) than the hybrid models.

Speech recognition is available in English, Spanish, French, German, Russian, Brazilian Portuguese, Korean, Japanese, Swahili, and Cambodian, though Cobalt is “always looking for partners to develop, sell, and/or market speech technology in other languages,” according to Cobalt Transcribe FAQs.

Other services include Cobalt Speech Intelligence, which analyzes audio to glean demographic information about speakers, such as age, gender, and regional accent, plus emotion.

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Investments and Intersections

As a consulting firm, Quansight specializes in solving data-related problems with open-source software and services, including AI, data and machine learning engineering, RAG, and large language models (LLMs), among others. 

Quansight, founded in 2018, has previously invested in pre-seed rounds for two other companies: Savimbo, a certifier of fair-trade carbon, biodiversity, and water credits; and Mod Tech Labs, an AI platform for 3D content creation. 

Quansight Initiate, an early-stage VC firm also headed by Oliphant, has invested in five open source tech startups since its 2019 founding.

“Quansight recently completed a restructuring of subsidiary companies,” Oliphant explained to Slator. “Going forward, M&A activities will focus on OpenTeams (for AI growth), OS BIG, Inc. dba OpenTeams Incubator (investment and M&A), Cobalt Speech and Language (speech and language technology and services), and Quansight, PBC to continue with the community-driven open-source aspect of its business.”

“All of our companies now have either existing or prospective intersections with the language industry,” he added.