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.
SC8380
推理时间： 3.79 ms
内存占用： 20 MB
NPU使用： 821 NPU
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
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SC8380
Source Model: MIT
Deployable Model: AI Model Hub License