HomeIoT ModelsWhisper-Base-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.

    Qualcomm® QCS8550
    QCS8550 (Proxy)
    Inference Time
    Memory Usage

    Technical Details

    Model checkpoint:base.en
    Input resolution:80x3000 (30 seconds audio)
    Mean decoded sequence length:112 tokens
    Number of parameters (WhisperEncoder):23.7M
    Model size (WhisperEncoder):90.6 MB
    Number of parameters (WhisperDecoder):48.6M
    Model size (WhisperDecoder):186 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 IoT Devices

    • QCS8550 (Proxy)

    Supported IoT Chipsets

    • Qualcomm® QCS8550