Whisper-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.
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
Licenses
Source Model:MIT
Deployable Model:AI Model Hub License
Tags
- foundation
Supported IoT Devices
- QCS8550 (Proxy)
Supported IoT Chipsets
- Qualcomm® QCS8550 (Proxy)
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