Aug 5, 2020 | Read time 2 min

The importance of languages for speech recognition

A diverse language offering is important for speech recognition providers, enabling customers to expand globally where previously this wouldn't be possible.
Header image

Roughly half the world speaks just one language – and very few people are fluent in more than two or three. Yet, Speechmatics’ any-context speech recognition engine can understand more than 30 different languages. From Spanish, Hungarian and Polish to Japanese, Russian and Korean, the list of our speech recognition languages spans the globe. To build and iterate languages faster than ever before, we developed an innovative machine learning framework – called The Automatic Linguist (AL).

A machine learning framework to rapidly build new languages

Most languages have inherent similarities in their fundamental sounds and grammatical structures. AL can recognize patterns within and across languages and apply these to a new language build – significantly reducing the time and data required to build new speech recognition languages. For example, AL enabled us to build Hindi in just a week.

AL won Speechmatics a Queen's Award for Enterprise in 2019 in the innovation category. But don't worry, Speechmatics’ technology isn't limited to the Queen's English – we operate in Global English, so you don't have to adjust the way you speak to be understood by our speech-to-text engine.

Whether you speak Australian English, American English, Jamaican English or African English, all you have to do is select our Global English language pack. We were the first company to do away with multiple language packs for different accents and dialects.

A global approach to understanding accents

In the UK alone there are about 56 main 'accent types'. The concept of having one language pack per accent or region is outdated in our increasingly connected and mobile world. We’ve all heard stories about people being misunderstood by their personal voice assistants – or closed captioning getting something awkwardly wrong.

Although very entertaining, these stories highlight a big issue. That's why Speechmatics’ Global English language pack encompasses all major English accents and dialects. Trained on thousands of hours of spoken data from more than 40 countries – and tens of billions of words drawn from global sources – our any-context speech recognition engine can cope with even the strongest accent. It also overcomes the industry-wide issue of handling multiple English accents in one recording.

But it's not just the variety of speech recognition languages and accents that's important for unlocking global value for our customers. Accuracy is also crucial – in all the languages we offer and in real-world situations such as noisy environments.

Accurately converting speech-to-text in multiple languages

Our world-leading machine learning algorithms can cope with anything from news subtitling or transcribing meeting notes to flagging up potential customer issues within a contact center. It's why our speech-to-text technology has been adopted by some of the largest blue-chip companies in the world.

We are already seeing a shift to a speech-enabled future where voice is the primary form of communication. The practical applications of our speech-to-text technology are now changing the way companies work – automating laborious tasks and unlocking the value of both live and recorded media.

So, what are you waiting for? Simply select Speechmatics and let the technology do the talking.

Latest Articles

[alt: Bilingual medical model featuring terms related to various health conditions and medications in Arabic and English. Key terms include "Chronic kidney disease," "Heart attack," "Diabetes," and "Insulin," among others, displayed in an organized layout.]
Product

Speechmatics achieves a world first in bilingual Voice AI with new Arabic–English model

Sets a new accuracy bar for real-world code-switching: 35% fewer errors than the closest competitor.

Speechmatics
SpeechmaticsEditorial Team
[alt: Illuminated ancient mud-brick structures stand against a dusk sky, showcasing architectural details and textures. Palm trees are in the foreground, adding to the setting's ambiance. Visually captures a historic site in twilight.]
Product

Your voice agent speaks perfect Arabic. That's the problem.

Most voice AI models are trained on formal Arabic, but real conversations across the Middle East mix dialects and English in ways those systems aren’t built to handle.

Yahia Abaza
Yahia AbazaSenior Product Manger
new blog image header
Technical

How Nvidia Dominates the HuggingFace Leaderboards in This Key Metric

A technical deep-dive into Token Duration Transducers (TDT) — the frame-skipping architecture behind Nvidia's Parakeet models. Covers inference mechanics, training with forward-backward algorithm, and how TDT achieves up to 2.82x faster decoding than standard RNN-T.

Oliver Parish
Oliver Parish Machine Learning Engineer
[alt: Healthcare professionals in scrubs and lab coats walk briskly down a hospital corridor. A nurse uses a tablet while others carry patient charts and attend to a gurney. The setting conveys a busy, clinical environment focused on patient care.]
Use Cases

Why AI-native EHR platforms will treat speech as core infrastructure in 2026

As clinical workflows become automated and AI-driven, real-time speech is shifting from a transcription feature to the foundational intelligence layer inside modern EHR systems.

Vamsi Edara
Vamsi EdaraFounder and CEO, Edvak EHR
[alt: Logos of Speechmatics and Edvak are displayed side by side, interconnected by a stylized x symbol. The background features soft, wavy lines in light blue, creating a modern and tech-focused aesthetic.]
Company

One word changes everything: Speechmatics and Edvak EHR partner to make voice AI safe for clinical automation at scale

Turning real-time clinical speech into trusted, EHR-native automation.

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