Tom Young

Digital Specialist

Open and closed captions serve different audiences and use cases. Here's what broadcasters and media distributors need to know — including compliance requirements and how speech-to-text technology makes both faster and more accurate.

[alt: Illustration showing the difference between open and closed captions on a broadcast monitor]

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Open Captioning vs Closed Captioning: The Complete Guide 

Closed Captioning vs Open Captioning in Media Distribution

Use Cases

Benedetta Cevoli

Senior Machine Learning Engineer

YouTube’s automated captioning service is notoriously unreliable and represents the dire need for innovation within the speech-to-text industry. Find out what we’re doing about it.

YouTube’s automated captioning service is notoriously unreliable and represents the dire need for innovation within the speech-to-text industry. Click to see what we’re doing about it.

YouTube’s Captions Represent the Dire Need for Speech-to-Text Innovation

YouTube’s Captions Represent the Direct Need for Speech-to-Text Innovation

Technical

Maithili Shinde

Technical Product Marketing Lead

Hyperscalers are a given – you’ve undoubtedly got one in your stack. Microsoft, Google, Amazon, and IBM; these companies are out to dominate both public and hybrid cloud services, and they aren’t afraid to expand into related verticals, either.

CCaaS v Hyperscalers blog image

Contact Centers rely on the best ASR - why are you settling for less?

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Editorial team

Contact centers are adopting speech-to-text technology to transform customer and agent interactions into data-driven insights and actionable outcomes.

Unlock value with Contact Center data

How to unlock value in contact center data with speech-to-text

Explore sample efficiency in the speech recognition industry. Discover cutting-edge techniques and benefits across industries. Unlock the potential of ASR.

Cambridge Science and Tech Wide Open Day

Sample Efficiency and What it Could Mean for Industry

Stuart Wood

Director, Product

Speechmatics breaks down language barriers of spoken communication in real-time with our brand new unified speech translation API for files and live audio. Find out more!

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Speechmatics Unified Speech Translation API is here

Product

Speech recognition technology is embedded in nearly every industry — from healthcare and banking to defence and media. Here are ten real-world examples of how it works, and why accuracy is everything.

[alt: Illustration showing real-world applications of speech and voice recognition technology across healthcare, automotive, legal, broadcast, and defense industries.]

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Real-World Examples of Speech and Voice Recognition Technology

Adam Walford

Senior Site Reliability Engineer

Speechmatics has recently switched from CPUs to GPUs to run most batch transcription models. Better hardware = increased accuracy. Find out more!

GPU Transcription Models

Autoscaling with GPU Transcription models

Headshot of Data Engineer, Steve Kingsley

Steve Kingsley

Data Engineer

Speechmatics’ ASR system (Ursa) surpasses competitors such as Amazon, Microsoft, and Google in real-time accuracy even when operating at a latency setting as low as 2s, while competitors are set to their highest latency, most accurate configurations. Furthermore, Ursa maintains near batch level performance across different latency requirements.

Best in class ASR system

Best-in-class real-time ASR system

Lawrence Atkins

Machine Learning Engineer

David MacLeod

Machine Learning Architect

Quantizing neural networks offers the promise of improved performance and efficiency, but achieving those gains on GPUs can be hard! This blog explains why, and shares solutions that we use in practice.

Fast and Accurate GPU Quantization for Transformers

Agent STT, powered by Linden 1, gives voice agents the speed, accuracy and conversational context they need in production.

Introducing Agent STT: built for the words that cost you the call

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Advanced speech recognition API with high accuracy across [<langcount>] languages.

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We are Speechmatics. Global experts in deep learning and voice technology. Accurate speech-to-text for analysis and accessibility.

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Global experts in deep learning and voice technology. Accurate speech-to-text for analysis and accessibility.

Stay up-to-date with the very latest product news, company news and artificial intelligence (AI) research. Bookmark our technology blog today!

Blog & Latest Speech Recognition News| Speechmatics

Ten questions to Stuart Wood, Director of Product, on the economics of speech at scale, how close local accuracy now gets to cloud, and who could benefit from Speechmatics On-Device.

On-device speech-to-text, in 10 questions

Scale more easily with Speechmatics 

End customers will only ever see their own provider's brand, which means the layer underneath has to be good enough to go unnoticed.

Tresic selects Speechmatics to power the speech layer of its conversation intelligence platform

On Arabic and English, Melia 1 runs at less than half the mixed error rate of the next best model. On Mandarin and Tamil it switches more accurately than anything else we tested.

Melia 1 leads speech-to-text code-switching in Arabic, Mandarin and Tamil

Latest

Quantization was the key to fitting a cloud-grade model on a laptop. Getting the full optimization chain to cooperate around it was the hard part.

Speechmatics versus Whisper: how Adobe Premiere's on-device speech engine got rebuilt

Company

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

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

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

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

The metrics, milestones, and real-world outcomes that defined Voice AI’s breakout year.

Speechmatics in 2025: the numbers that shaped Voice AI's breakthrough year (+ what’s to come in 2026) 

Ship Voice AI agents that understand every voice in real-time, even in noisy, multi-speaker scenarios.

Vapi and Speechmatics: Build agents that understand every voice

Real-time voice AI isn’t just about speed — it’s about handling thousands of live conversations at once. Here’s why concurrency makes or breaks performance at scale.

The scaling challenge voice AI can’t ignore

Linden, Speechmatics' new speech-to-text model built for voice agents, is now available through LiveKit Inference, no separate API key, account, or invoice required. Try it out now, click the circle to the bottom right of your screen.

Speechmatics & LiveKit Inference target the accuracy gap that breaks voice agents in production

Speechmatics is now live on Zapier. Connect industry-leading speech-to-text to 8,000+ apps with no code.

Speechmatics on Zapier: No-Code Speech-to-Text Automation

With 93% accuracy, our new model is twice as good as the nearest competitor.

Speechmatics launches Medical Model for real-time clinical transcription

Because in the real world, conversations are messy, and Voice AI needs to keep up.

Speaker Focus: Fixing Voice AI for the real world

A multilingual speech-to-text model from Speechmatics, with code-switching across [<langcount>] languages. Available today in production preview, starting with batch transcription.

Introducing Melia, our new multilingual speech-to-text model

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.

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

A new integration gives agent developers a QA layer built for the complexity of the real world.

Speechmatics and Cekura bring real-world STT testing to voice agent pipelines

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

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

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.

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

An hour of audio in, a transcript back in under 20 seconds. 30 minutes in under 10 seconds. 10 minutes in under 5 seconds.

Gone in 20 seconds: Melia outpaces AssemblyAI, ElevenLabs and Soniox

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

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

Voice agents that pass in demos routinely fail in production. This guide covers the 11 best voice agent testing platforms in 2026, with the Five-Layer Testing Framework, platform deep dives, open-source alternatives, and a decision guide by maturity stage.

De-risk your voice agent: The 11 best voice agent testing platforms in 2026

Build a cleaner path between batch and real time. Learn when micro-batching makes sense, how to chunk audio, submit jobs, stitch JSON, and scale safely with the Speechmatics API.

How to build a microbatching workflow with the Speechmatics API

How Wellcom Health uses real-time transcription, medical-grade accuracy and diarization to turn messy Dutch consultations into validated clinical reports.

Dutch doctors spend a quarter of their day on admin. Wellcom has built the fix.

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.

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

The court reporter shortage is reshaping litigation. Explore data, causes, and how legal teams are using digital reporting and AI transcription to adapt.

The court reporter shortage crisis: data, causes, and what legal teams are doing about it

Word error rate for legal transcription has no single acceptable threshold. But knowing how accuracy, audio quality, and review obligations connect to real legal risk is what separates a reliable transcript from a costly one.

What Word Error Rate Is Acceptable for Legal Transcription?

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.

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

What teams deploying Voice AI at scale see coming next as production pressure reshapes adoption.

7 Voice AI predictions from teams building at scale in 2026

Voice AI moved fast. Regulation caught up. Here’s how to stay compliant in 2026.

Your essential 2026 guide to voice ai compliance in today's digital landscape

Faceless YouTube channels are becoming a scalable, system-driven way for businesses to produce high-impact video without relying on on-camera talent.

How to Launch a Faceless YouTube Channel Using AI Voiceover (Business Guide)

The quiet consulting room was just the warm-up. Emergency departments, ambulances, and operating theatres are the real test, and they're next.