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Translate and Transcribe Audio with Whisper
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➡️ In this tutorial, you'll learn how to translate and transcribe audio to English using Whisper and the Takomo builder.
🔗 Important Links
- Takomo AI
- Discord
- Twitter
❓ What is Whisper?
Whisper is a general-purpose speech recognition model. 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.
Discover the power of Whisper, a robust and general-purpose speech recognition model developed by OpenAI. Whisper is a multilingual model that not only excels in speech recognition but also performs speech translation and language identification, making it a highly versatile tool.
Built using a Transformer sequence-to-sequence model, Whisper is trained on various speech processing tasks. These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, enabling a single Whisper model to replace many stages of a traditional speech-processing pipeline.
Whisper offers five model sizes, each with English-only versions, providing a balance between speed and accuracy. The models have different memory requirements and relative speeds, making it flexible to suit various application needs1. Whisper can easily transcribe speech in audio files and also perform transcriptions within Python, offering a practical solution for developers and researchers alike.
In addition, Whisper provides lower-level access to the model, allowing users to detect the spoken language and decode the audio. This enhances its usability for more complex applications and research purposes.
Notably, Whisper's code and model weights are released under the MIT License, endorsing its commitment to open-source principles and promoting innovation in the field of speech recognition and beyond.
🔗 Important Links
- Takomo AI
- Discord
❓ What is Whisper?
Whisper is a general-purpose speech recognition model. 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.
Discover the power of Whisper, a robust and general-purpose speech recognition model developed by OpenAI. Whisper is a multilingual model that not only excels in speech recognition but also performs speech translation and language identification, making it a highly versatile tool.
Built using a Transformer sequence-to-sequence model, Whisper is trained on various speech processing tasks. These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, enabling a single Whisper model to replace many stages of a traditional speech-processing pipeline.
Whisper offers five model sizes, each with English-only versions, providing a balance between speed and accuracy. The models have different memory requirements and relative speeds, making it flexible to suit various application needs1. Whisper can easily transcribe speech in audio files and also perform transcriptions within Python, offering a practical solution for developers and researchers alike.
In addition, Whisper provides lower-level access to the model, allowing users to detect the spoken language and decode the audio. This enhances its usability for more complex applications and research purposes.
Notably, Whisper's code and model weights are released under the MIT License, endorsing its commitment to open-source principles and promoting innovation in the field of speech recognition and beyond.
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