Feb 20, 2018 | Read time 3 min

Speechmatics launches Global English, an accent-agnostic language pack for speech-to-text transcription

languages 4
When tested against providers of similar solutions, GE consistently produced more accurate transcriptions. Compared directly, GE was between 3% and 55% more accurate than all Google’s Cloud Speech API accent-specific language packs and between 5% and 23% more accurate than IBM’s Cloud US English language pack*.

It supports every major English accent providing a consistent and cost-effective solution Today, Speechmatics is announcing the launch of Global English, a single English language pack supporting all major English accents for use in speech-to-text transcription. Global English (GE) was trained on thousands of hours of spoken data from over 40 countries and tens of billions of words drawn from global sources, making it one of the most comprehensive and accurate accent-agnostic transcription solutions on the market.

Traditionally, speech recognition has dealt with variations in language by producing a different language pack for every distinct accent or region. However, this meant a whole new set of models trained on data from that particular subset of speakers of the languages. With the launch of GE, Speechmatics is aiming to democratise speech-to-text transcription to overcome industry-wide issues where there are multiple English accents in one recording. Thus, providing a far more accurate, consistent and cost-effective solution. Speech recognition has advanced hugely in recent years, making GE possible. The team has been gathering data from a wide range of sources and taking advantage of the astonishing rise in computer power, allowing them to train bigger models, based on more data, capable of supporting more variations. Speechmatics has now built 72 unique languages, more than any other provider on the market, including Amazon, Google, Nuance, Microsoft and IBM. With the modern neural network architectures capable of generalising across variations in speech by using representation learning, Speechmatics were able to generate the accuracy of multiple specialised models all in one language pack.

Benedikt von Thüngen, CEO at Speechmatics, explained:

“At Speechmatics, we have historically produced North American, British and Australian versions of the English language packs, as well as domain-specific language packs. Applications include broadcast, compliance, speech analytics, call recording and meeting transcription among others. While a traditional British language pack does indeed perform better on British accented speech than say, a traditional North American language pack would, there’s still tens of distinct British accents to address. And so, we realised we need to come up with what we like to call ‘One Model to Rule Them All’ – an accent-agnostic language pack that is just as accurate at transcribing Australian accent as it is with Scottish.”

Tom Ash, Speech Recognition Director at Speechmatics and winner of the ‘Speech Luminary’ award, commented:

“In the UK alone, there are about 56 main ‘accent types’, and the concept of having one language pack per accent or region is very outdated. Bearing in mind that we live in an increasingly connected and mobile world, we need our tech to reflect that. We’ve all heard stories about people being misunderstood by their personal voice assistants or closed captioning getting something awkwardly wrong. While a lot of these stories are humorous, it’s ultimately highlighting a big issue. We’re hoping that Global English will inspire others to become more flexible and fair when it comes to people’s accents.”

Try it now Download infographic Download whitepaper *Test sets comprised of approximately 4 hours of diverse audio and transcribed text. Accented test files included variations in gender, age and region. We know accuracy results are always dependant on the test set used. If you would like to know further details about our test set, please get in touch.

Latest Articles

Carousel slide image
Product

Alphanumeric speech recognition: why voice assistants mangle SKUs (and how to fix it)

A guide for voice AI engineers, ecommerce platforms and warehouse teams on SKU recognition accuracy voice assistant deployments depend on: why speech recognition systems produce transcription errors on product codes, what to measure when error rates matter, and the fixes that move the needle on order picking, voice ordering and customer-facing voice AI.

Speechmatics
SpeechmaticsEditorial Team
Carousel slide image
Technical

The Adobe story: How we made cloud-grade AI work on your laptop

Behind the build: what it takes to make cloud-grade speech recognition work inside Adobe Premiere, and why Whisper raised the stakes.

Andrew Innes
Andrew InnesChief Architect
Carousel slide image
Company

Adobe and Speechmatics deliver cloud-grade speech recognition on-device for Premiere

Adobe Premiere users can run the most accurate on-device transcription locally; efficient enough for a laptop, powerful enough for professional work.

Speechmatics
SpeechmaticsEditorial Team
Carousel slide image
Use Cases

Best speech-to-text AI guide: APIs, platforms and services compared

Speech-to-text has moved from novelty to enterprise infrastructure. Here's how the leading platforms stack up in 2026 — and how to pick the right one.

Tom Young
Tom YoungDigital Specialist
Speechmatics x Thymia combine medical-grade speech-to-text with clinical-grade voice biomarker intelligence to identify health signals.
News

AI can now understand health signals from 15 seconds of your voice, including fatigue, stress and type 2 diabetes

The joint platform returns transcription and health signals in real time, with no additional hardware required.

Speechmatics
SpeechmaticsEditorial Team
[alt: Concentric circles radiate outward from a central orange icon with a white Speechmatics logo. The background is dark blue, enhancing the orange glow. A thin green line runs horizontally across the lower part of the image.]
Technical

Speed you can trust: The STT metrics that matter for voice agents

What “fast” actually means for voice agents — and why Pipecat’s TTFS + semantic accuracy is the clearest benchmark we’ve seen.

Archie McMullan
Archie McMullanSpeechmatics Graduate