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Whisper GitHub

★2.2
💬179
💲Free

Whisper is an open-source speech recognition model that enables accurate transcription of audio files into text. It supports multiple languages and can perform speech translation and language identification. The model is available in various sizes, offering different trade-offs between speed and accuracy. It can be used via command-line or Python APIs, making it versatile for developers and non-developers.

💻
Platform
web
Audio transcriptionLanguage identificationMultilingualOpenAISpeech recognitionSpeech translationTransformer model

What is Whisper GitHub?

Whisper is a general-purpose speech recognition model developed by OpenAI. It is designed for multilingual speech recognition, speech translation, and language identification. The model uses a Transformer sequence-to-sequence architecture trained on diverse audio data, allowing it to replace multiple stages of traditional speech processing pipelines. Whisper supports both command-line and Python usage, making it accessible for developers and end-users alike.

Core Technologies

  • Transformer model
  • Sequence-to-sequence model
  • Multitask learning

Key Capabilities

  • Speech to text conversion
  • Multilingual support
  • Speech translation
  • Language identification
  • Voice activity detection

Use Cases

  • Transcribing audio files to text
  • Translating speech between languages
  • Identifying the language spoken in an audio file
  • Automating voice-based workflows
  • Enhancing accessibility for users with hearing impairments

Core Benefits

  • High accuracy in speech recognition
  • Supports multiple languages
  • Can perform speech translation
  • Open-source and free to use
  • Available for both command-line and Python usage

Key Features

  • Multilingual speech recognition
  • Speech translation
  • Language identification
  • Voice activity detection
  • Multiple model sizes for performance trade-offs

How to Use

  1. 1
    Install Whisper using pip: `pip install -U openai-whisper`.
  2. 2
    Install required dependencies like ffmpeg and Rust if needed.
  3. 3
    Use the command-line tool with the audio file and model size: `whisper audio.flac --model medium`.
  4. 4
    Alternatively, load the model in Python and call the transcribe() method on an audio file.

Frequently Asked Questions

Q.What is Whisper?

A.Whisper is a general-purpose speech recognition model developed by OpenAI. It can perform multilingual speech recognition, speech translation, and language identification.

Q.How do I install Whisper?

A.You can install Whisper using pip: `pip install -U openai-whisper`. You also need to install ffmpeg and may need Rust.

Q.What model sizes are available?

A.There are five model sizes: tiny, base, small, medium, and large. Each offers different speed and accuracy tradeoffs.

Q.How do I transcribe an audio file?

A.You can use the command-line tool: `whisper audio.flac audio.mp3 audio.wav --model medium` or use the Python API.

Pros & Cons (Reserved)

✓ Pros

  • High accuracy in speech recognition
  • Supports multiple languages
  • Can perform speech translation
  • Available for both command-line and Python usage
  • Open-source and free to use (MIT License)

✗ Cons

  • Requires installation of ffmpeg
  • May require Rust installation for certain platforms
  • Performance varies depending on the language
  • Larger models require significant VRAM

Alternatives

No alternatives found.