IBM Watson Speech To Text vs Rev.ai comparison

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Featured Review
Anonymous User
Ranking
4th
Views
2,508
Comparisons
1,859
Reviews
0
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0
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6th
Views
326
Comparisons
259
Reviews
0
Average Words per Review
0
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N/A
Comparisons
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Rev.ai
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Overview

Watson Speech to Text is a cloud-native solution that uses deep-learning AI algorithms to apply knowledge about grammar, language structure, and audio/voice signal composition to create customizable speech recognition for optimal text transcription.

Founded in 2020, REVAI s mission is to encourage Doctors and Clinics to start making anonymized data available for open research, while prompting citizens to become the ultimate owners and controllers of their health data. REVAI is intended to become a true information marketplace, based on new mechanisms of trust and direct, value-based relationships between citizens, hospitals, research centres and businesses.

Sample Customers
American Airlines, UBank, Bitly, Eurobits
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Top Industries
VISITORS READING REVIEWS
Computer Software Company22%
University10%
Educational Organization9%
Comms Service Provider8%
No Data Available
Company Size
VISITORS READING REVIEWS
Small Business24%
Midsize Enterprise13%
Large Enterprise62%
No Data Available

IBM Watson Speech To Text is ranked 4th in Speech-To-Text Services while Rev.ai is ranked 6th in Speech-To-Text Services. IBM Watson Speech To Text is rated 8.0, while Rev.ai is rated 0.0. The top reviewer of IBM Watson Speech To Text writes "Easy to understand, configure, and use". On the other hand, IBM Watson Speech To Text is most compared with Google Cloud Speech-to-Text, Microsoft Azure Speech Service, Amazon Transcribe and AssemblyAI, whereas Rev.ai is most compared with Amazon Transcribe and AssemblyAI.

See our list of best Speech-To-Text Services vendors.

We monitor all Speech-To-Text Services reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.