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HomeCompute ModelsWhisper-Small-En


Automatic speech recognition (ASR) model for English transcription as well as translation.

OpenAI’s Whisper ASR (Automatic Speech Recognition) model is a state-of-the-art system designed for transcribing spoken language into written text. It exhibits robust performance in realistic, noisy environments, making it highly reliable for real-world applications. Specifically, it excels in long-form transcription, capable of accurately transcribing audio clips up to 30 seconds long. Time to the first token is the encoder's latency, while time to each additional token is decoder's latency, where we assume a mean decoded length specified below.

Snapdragon® X Elite
Inference Time
Memory Usage

Technical Details

Model checkpoint:small.en
Input resolution:80x3000 (30 seconds audio)
Mean decoded sequence length:112 tokens
Number of parameters (WhisperEncoder):102M
Model size (WhisperEncoder):390 MB
Number of parameters (WhisperDecoder):139M
Model size (WhisperDecoder):531 MB

Applicable Scenarios

  • Smart Home
  • Accessibility


Source Model:MIT
Deployable Model:AI Model Hub License


  • foundation
    A “foundation” model is versatile and designed for multi-task capabilities, without the need for fine-tuning.

Supported Compute Chipsets

  • Snapdragon® X Elite