Speechmatics is a Voice AI company that provides highly accurate, real-time speech-to-text and text-to-speech APIs supporting over 55 languages. Their technology is built on deep neural networks and is designed to understand diverse accents and dialects, making it one of the most inclusive speech recognition platforms. The company offers a speech intelligence suite including summarization, sentiment analysis, and topic detection, and is compliant with GDPR, HIPAA, and SOC 2. With $7.5M in funding, Speechmatics serves enterprises across media, healthcare, contact centers, and education.
Low-latency speech-to-text for multilingual, multi-speaker conversations.
Voice agent builders with sub-second, speaker-aware STT and TTS across 56+ languages.
Text-to-speech service for voice applications.
Real-time speech-to-text with high accuracy and low latency.
On-device speech recognition for privacy-sensitive deployments.
Enterprise-grade speech technology with security and compliance.
Multilingual speech-to-text model with code-switching across 56+ languages.
Medical speech recognition model that reduces errors on key terms by up to 50%.
Speechmatics has announced the release of its Melia-1 speech-to-text model, which the company claims achieves a 206x speed factor on the Artificial Analysis leaderboard. The model is designed to enable near-real-time transcription for media production and contact center workflows without requiring audio chunking.
Speechmatics published a detailed post on how it rebuilt Adobe Premiere’s on-device speech engine, saying its model outperformed Whisper on the same hardware and was optimized to run on consumer laptops.
Speechmatics details the engineering process behind updating its speech-to-text engine for Adobe Premiere to maintain competitive performance against OpenAI's Whisper model on consumer hardware. The article focuses on technical techniques like quantization, custom model optimization scripts, and GPU acceleration to manage resource constraints on personal computers.
Speechmatics has launched Melia, a new multilingual speech-to-text model capable of handling code-switching across 56+ languages. The model is available in production preview via batch processing and is positioned as a cost-effective solution for contact center analytics and broadcast captioning.
Media Track, a global media monitoring company, has enhanced its broadcast and print transcription accuracy and scalability by integrating Speechmatics' real-time speech-to-text technology. This partnership allows Media Track to improve its global media monitoring capabilities.
NCI has implemented Speechmatics' advanced speech recognition technology to enhance its real-time captioning services. The partnership aimed to revolutionize captioning by addressing existing challenges and improving efficiency. The article highlights the solutions implemented and the positive outcomes of this collaboration between the two companies.
AI-Media is enhancing its live captioning capabilities by integrating Speechmatics' advanced transcription engine. This collaboration aims to deliver accurate, scalable, and multilingual real-time captions for global media and educational content.
Speechmatics and Adobe have collaborated to introduce cloud-grade speech recognition directly on-device within Adobe Premiere. This new feature enables private, offline, and accurate speech-to-text capabilities for professional creators using Premiere.
The article discusses the crucial metrics for speech-to-text latency in voice agents, focusing on Time-To-First-Speech (TTFS) and accuracy. It highlights how Pipecat's benchmarks are influencing the conversation around these metrics.
Speechmatics announced new real-time, speaker-aware Voice Agents developed in partnership with LiveKit. The integration aims to enhance the accuracy of AI agents by 25% in real time, supporting natural, inclusive, and reliable speech AI. This collaboration focuses on enabling AI agents to understand speaker identity.
