Rev AI

Transcribe audio and video files in minutes with flexible options for asynchronous, streaming, and human transcription, supporting over 58 languages and advanced NLP features.
Speech-to-Text Natural Language Processing Transcription Services

Rev AI is a speech-to-text API with a strong reputation for accuracy and flexibility, with a range of options for different use cases, including asynchronous, streaming and human transcription.

The asynchronous speech-to-text option lets you upload audio or video files and get machine-generated transcripts in minutes. It works with more than 58 languages. The streaming option produces transcripts as audio is being recorded, working with nine languages. For better quality, you can also hire a human to transcribe the audio, with a 24-hour turnaround time, at least for now, only for English.

Other options include language identification, sentiment analysis, topic extraction, summarization and translation. Forced alignment gives you precise timestamps to make content more searchable and analyzable.

Rev AI is designed to have low bias, meaning it works well regardless of accent, gender or ethnicity. It also works with multiple languages and offers the full range of speech-to-text and NLP tools. The service is secured with standards like SOC II, HIPAA, GDPR and PCI.

Pricing is based on usage, with machine transcription costing $0.02 per minute, human transcription costing $1.50 per minute, and other options costing accordingly. The service also offers free credits worth about five hours of machine transcription, and it can handle common media formats.

For heavy usage, contact Rev AI for enterprise pricing and dedicated account management. The service is geared for developers, with detailed documentation and SDKs to integrate the service.

Whether you're in the media and entertainment industry, education, call centers or other areas, Rev AI offers a service to convert speech to text and to use NLP techniques. It's geared for businesses that want to improve accessibility, efficiency and customer satisfaction.

Published on July 6, 2024

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