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What is Rev AI?

Rev AI is a speech-to-text API platform built for developers who need accurate, scalable, and fast transcription. The platform converts prerecorded audio files into transcripts and also supports real-time transcription from streaming audio. Rev AI supports more than 57 languages with grammar, punctuation, formatting, and consistently low word error rates. Its proprietary speech recognition models are trained on a carefully selected subset of more than 7 million hours of human-verified speech data. The platform is designed to deliver strong accuracy across many use cases, speakers, accents, nationalities, genders, and ethnic backgrounds. Developers can get started quickly with Rev AI’s API, SDKs, documentation, and support. The platform supports cloud and on-premises deployment for teams with different infrastructure and security needs. Rev AI includes AI Insights that help teams go beyond transcription through language identification, sentiment analysis, topic extraction, summarization, and translation. Its forced alignment and precision timestamp capabilities provide word-level timing for searchability, accessibility, media workflows, and content indexing. Enterprise-grade security features include SOC II, HIPAA, GDPR, and PCI compliance, 99.99% uptime, and encryption at rest and in transit. By combining accurate speech-to-text, real-time streaming, multilingual coverage, developer tools, AI insights, precision timestamps, and enterprise security, Rev AI helps organizations turn spoken content into reliable data.

What is MAI-Transcribe-2-Streaming?

MAI-Transcribe-2-Streaming stands as an innovative solution in the realm of low-latency streaming transcription, specifically tailored for real-time voice applications and boasting the ability to generate transcripts in an impressive 60 languages, complete with automatic, ongoing language identification. Rather than requiring the entirety of speech to be finished, this model can produce initial partial transcripts in a mere 100 milliseconds after receiving audio input, allowing it to progressively refine and enhance these transcripts as more context is received, thus stabilizing the text rapidly. This capability empowers voice applications to begin analyzing data, employing tools, or displaying live transcripts even while the speaker continues to talk, significantly improving the overall user experience. Microsoft reports that this model has achieved the highest rankings for both final and partial transcript accuracy in Artificial Analysis assessments. To further elevate the user experience, MAI-Voice-2.1 introduces a multilingual text-to-speech feature that covers 23 languages and 26 locales, allowing a single voice to effortlessly switch between languages while maintaining the speaker's identity and adopting local accents. This advanced integration not only enhances the functionality of speech applications but also broadens their accessibility to a wider range of users, making it invaluable for diverse audiences. Furthermore, such advancements in technology pave the way for improved communication in multilingual environments, highlighting the importance of inclusivity in modern speech applications.

Media

Media

Integrations Supported

Quickwork
Rev
Workers by Delos

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub

Company Facts

Organization Name

Rev

Date Founded

2010

Company Location

United States

Company Website

www.rev.ai/

Company Facts

Organization Name

Microsoft AI

Date Founded

2024

Company Location

United States

Company Website

microsoft.ai/news/our-first-streaming-transcription-model/

Categories and Features

Speech Recognition

Not specified

Speech to Text

Not specified

Categories and Features

AI Models

Not specified

Speech to Text

Not specified

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