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OpenAI Whisper — general-purpose speech recognition. Multilingual transcription, translation to English, and speaker-agnostic ASR. Models from tiny to large. Robust to noise, accents, and technical vocabulary.
Passed 22 of 22 test cases with the skill, and 20 of 22 without it.
2 fixed20 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the specific bash CLI command to install the speech recognition library using the uv package manager?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies uv pip install openai-whisper | Missed | Passed |
The instructions your model reads when the skill loads.
OpenAI Whisper is a general-purpose speech recognition model supporting multilingual transcription, translation to English, and speaker-agnostic ASR. Models range from tiny (39M params) to large (1.55B params). Robust to noise, accents, and technical vocabulary.
uv pip install openai-whisper
ffmpeg # required for audio loading
import whisper
model = whisper.load_model("base")
result = model.transcribe("audio.mp3")
print(result["text"])
# Transcribe in original language
result = model.transcribe("french_audio.mp3", language="fr")
# Translate to English
result = model.transcribe("german_audio.mp3", task="translate")
print(result["text"]) # English output
result = model.transcribe("lecture.mp3", word_timestamps=True)
for segment in result["segments"]:
for word in segment["words"]:
print(f"{word['word']}: {word['start']:.2f}-{word['end']:.2f}")
test cases passed, vs 20 / 22 without
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