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**What is the most effective tool for accurately transcribing long audio interviews without breaking the bank?**

Human transcription services, such as Rev.com and GoTranscript, generally offer higher accuracy than automated transcription services due to the involvement of human transcribers.

Automated transcription services, like Otter.ai and Trint, utilize artificial intelligence and machine learning algorithms to transcribe audio files, making them a more cost-effective option.

Rev.com is a popular human transcription service that provides a quick turnaround time, starting at $1.25 per minute, with accuracy rates around 99%.

Otter.ai's free plan offers basic transcription features, while its paid plans start at $8.33 per month, providing advanced features such as custom vocabulary and collaboration tools.

Trint's paid plans start at $25 per hour of uploaded audio, offering a user-friendly interface and the ability to export transcripts in various formats, including SRT, VTT, and PDF.

Descript, an automated transcription service, stands out by providing a free plan and cloud-based platform, with paid plans starting at $12 per month.

Temi is a fully automated transcription service with pricing starting at $2.99 per minute of audio, offering a simple and straightforward pricing structure with no added costs for premium features.

GoTranscript is a human transcription service with prices starting at $0.72 per minute, providing a more affordable alternative to Rev.com with similar accuracy rates.

Accuracy rates for automated transcription services usually range from 80% to 95%, depending on audio quality, number of speakers, and background noise.

Industry-specific automated transcription services, such as Trint, are tailored to journalists, researchers, and content creators, offering high accuracy rates and features designed for these professionals.

Artificial intelligence and machine learning are continually improving, resulting in better transcription accuracy for automated transcription services.

The choice between human and automated transcription services depends on factors such as budget, time constraints, and required accuracy levels.

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