{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Whisper performs multilingual speech recognition, speech translation, and language identification using a Transformer model trained on diverse audio data.","skillfed_tags":["speech-recognition","multilingual","audio-processing"],"use_cases":["Transcribe English audio files quickly using the turbo model for real-time or batch processing","Translate non-English speech to English by specifying language and task parameters","Identify the spoken language in an audio file before further processing","Build a speech-to-text pipeline that handles multiple languages with a single model","Process audio in Python with fine-grained control via lower-level APIs like detect_language() and decode()"],"what_it_does":"Whisper is OpenAI's general-purpose speech recognition model that transcribes, translates, and identifies languages in audio. It uses a Transformer sequence-to-sequence architecture trained on diverse multilingual audio data, allowing a single model to handle multiple speech-processing tasks that traditionally required separate pipeline stages. The model comes in six sizes (tiny, base, small, medium, large, turbo) with English-only and multilingual variants, offering speed-accuracy tradeoffs from ~1 GB to ~10 GB VRAM.\n\nYou can use it via command-line (e.g., `whisper audio.mp3 --model turbo`) or Python API. It processes audio in 30-second sliding windows and supports language specification and translation tasks. Installation requires torch, numba, triton, and other heavy numerical libraries, plus ffmpeg on your system. The package is actively maintained and has no known vulnerabilities.","worth_installing":"Yes, if you have the system dependencies and can tolerate high install friction. Whisper is actively maintained, permissively licensed, widely used (top 5000 packages), and has no known vulnerabilities. The heavy numerical dependencies (torch, numba, triton) are unavoidable for the task. Install only if you need multilingual speech recognition or translation; for English-only transcription, smaller or specialized models may be more practical."},"id":"openai-whisper","links":{"html":"https://skillfed.io/packages/openai-whisper","md":"https://skillfed.io/packages/openai-whisper.md","pypi":"https://pypi.org/project/openai-whisper/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-06-26","license_spdx":null,"license_treatment":"permissive","name":"openai-whisper","python_support":"supports_current","summary":"Robust Speech Recognition via Large-Scale Weak Supervision"},"popularity":{"monthly_downloads":4241268,"position":2355,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"20250625"}