Audience
Users, developers and teams that need accurate, multilingual, context-aware transcription for voice agents, meetings, call analytics, accessibility, and content workflows
About MAI-Transcribe-1.5
MAI-Transcribe-1.5 is Microsoft AI’s production-ready speech-to-text model for turning noisy audio into highly accurate, domain-aware transcripts across 43 languages. It delivers consistent, high-accuracy transcription across languages, accents, speaking styles, and challenging audio conditions, with automatic language detection included. The model is designed for real-world audio where speech often comes through conference rooms, phone lines, busy streets, low-quality recordings, background noise, and overlapping speakers. MAI-Transcribe-1.5 adapts transcription to domain-specific terminology, making it ready for captions, call analysis, accessibility, meeting transcription, doctor’s notes, pharma customer calls, content workflows, and other enterprise speech use cases out of the box. It uses contextual biasing to improve recognition of specialized vocabulary, names, industry language, and terms that generic transcription systems may miss.
Other Popular Alternatives & Related Software
MAI-Transcribe-1
MAI-Transcribe-1 is a state-of-the-art speech-to-text model developed by Microsoft and available through Azure AI Foundry, designed to deliver high-accuracy transcription for real-world audio across enterprise and developer use cases. It supports 25 major languages and is optimized to handle diverse accents, dialects, and speaking styles, maintaining consistent performance even in challenging conditions such as background noise, low-quality recordings, or overlapping speech. It is built by Microsoft’s AI Superintelligence team with a dual focus on accuracy and efficiency, enabling fast batch transcription and scalable deployment for production environments. MAI-Transcribe-1 powers a wide range of applications, including meeting transcription, live captions, accessibility tools, call center analytics, and voice-driven agents, making it a foundational component for voice-enabled systems.
Learn more about MAI-Transcribe-1
Amazon Transcribe
Amazon Transcribe makes it easy for developers to add speech to text capabilities to their applications. Audio data is virtually impossible for computers to search and analyze. Therefore, recorded speech needs to be converted to text before it can be used in applications. Historically, customers had to work with transcription providers that required them to sign expensive contracts and were hard to integrate into their technology stacks to accomplish this task. Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy. Amazon Transcribe uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately. Amazon Transcribe can be used to transcribe customer service calls, automate subtitling, and generate metadata for media assets to create a fully searchable archive.
Learn more about Amazon Transcribe
Speechmatics
Best-in-Market Speech-to-Text & Voice AI for Enterprises.
Speechmatics delivers industry-leading Speech-to-Text and Voice AI for enterprises needing unrivaled accuracy, security, and flexibility. Our enterprise-grade APIs provide real-time and batch transcription with exceptional precision—across the widest range of languages, dialects, and accents.
Powered by Foundational Speech Technology, Speechmatics supports mission-critical voice applications in media, contact centers, finance, healthcare, and more. With on-prem, cloud, and hybrid deployment, businesses maintain full control over data security while unlocking voice insights.
Trusted by global leaders, Speechmatics is the top choice for best-in-class transcription and voice intelligence.
🔹 Unmatched Accuracy – Superior transcription across languages & accents
🔹 Flexible Deployment – Cloud, on-prem, and hybrid
🔹 Enterprise-Grade Security – Full data control
🔹 Real-Time & Batch Processing – Scalable transcription
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Microsoft Frontier Tuning
Microsoft Frontier Tuning lets organizations customize one or more of Microsoft’s top MAI models around their unique business needs, trained safely within their own secure environment instead of relying on a generic AI model. The process starts by defining the task and what success looks like, then feeding in data, workflows, and expertise from Microsoft 365 and beyond. Performance is improved through training and iterative optimization, then deployed in Microsoft Foundry or Copilot, where the model can continue improving from real usage. Microsoft Frontier Tuning is designed to create models that know the organization’s work, terms, context, processes, and expertise while keeping data private and secure inside the customer’s environment. It gives teams more control over the model, avoids vendor lock-in, and helps them squeeze more value from every dollar spent by delivering frontier performance with superior token efficiency.
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Integrations
Company Information
Microsoft AI
Founded: 2024
United States
microsoft.ai/news/mai-transcribe-1-5more-accurate-context-aware-and-built-for-production/
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Product Details
Platforms Supported
Cloud
Training
Documentation
Support
Online
MAI-Transcribe-1.5 Frequently Asked Questions
Q: What kinds of users and organization types does MAI-Transcribe-1.5 work with?
MAI-Transcribe-1.5 works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does MAI-Transcribe-1.5 support in their product?
MAI-Transcribe-1.5 supports these languages: English.
Q: What kind of support options does MAI-Transcribe-1.5 offer?
MAI-Transcribe-1.5 offers support via online.
Q: What other applications or services does MAI-Transcribe-1.5 integrate with?
MAI-Transcribe-1.5 integrates with: Microsoft Foundry and Microsoft Azure.
Q: What type of training does MAI-Transcribe-1.5 provide?
MAI-Transcribe-1.5 provides training in the form of documentation.
