ATC to Text

What is ATC to Text ?

ATC to Text is an AI-powered tool designed to transcribe podcast audio into text with high accuracy. It leverages advanced Whisper Med technology, fine-tuned specifically for ATC radio content, to deliver precise and reliable transcriptions. Whether you're a content creator, journalist, or professional, this tool helps you convert spoken words into readable text efficiently and without losing essential details.

Features

• High-Accuracy Transcriptions: Fine-tuned for ATC radio audio, ensuring accurate results. • Long Audio Support: Easily handles extended podcast recordings without compromising quality. • User-Friendly Interface: Simple and intuitive, making it accessible to all users. • Timestamps Included: Provides timestamps for easy referencing of specific audio segments. • Multi-Language Support: Transcribes audio in multiple languages for global accessibility. • Cloud-Based: No need for heavy installations or downloads.

How to use ATC to Text ?

1. Upload Your Audio File: Select and upload your podcast audio file (supported formats include MP3, WAV, etc.).
2. Select Language: Choose the language of your audio for accurate transcription.
3. Start Transcription: Click the "Transcribe" button to begin the process.
4. Receive Transcription: Wait for the transcription to complete (may take a few minutes for longer files).
5. Review and Export: Review the transcribed text and export it in formats like TXT, DOCX, or PDF for further use.

Frequently Asked Questions

What file formats does ATC to Text support?
ATC to Text supports common audio formats such as MP3, WAV, and AAC. For a full list of supported formats, refer to the app's documentation.

How long does transcription take?
Transcription time depends on the length and quality of the audio. Short files are processed in seconds, while longer recordings may take several minutes.

Is my data secure?
Yes, ATC to Text prioritizes your privacy. All uploaded files and transcriptions are encrypted and deleted from the server after processing.