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It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. In this article, you learn about the whisper model from openai that you can use for speech to text and speech translation. Perfect for meetings, interviews, and legal transcription.
Transforming audio into text is now simpler and more accurate, thanks to openai’s whisper This article delves into the world of whisper, offering a comprehensive guide on how to harness its capabilities for audio transcription in python, all without the need for external apis. This article will guide you through using whisper to convert spoken words into written form, providing a straightforward approach for anyone looking to leverage ai for efficient transcription.
Upload or record an audio file, or provide a youtube video link to convert it into text
Choose between transcribing or translating the audio. This guide will walk you through the various whisper models, their differences, and how to select the right one for your specific use case. Whisper comes in various sizes, each representing a different tradeoff between accuracy, speed, and resource requirements.
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