Audio & Video
Label audio and video files in-house for tasks such as speaker diarization and classification. Use Prodigy’s fully scriptable back-end to build powerful workflows by putting your model in the loop.
Fast and flexible annotation
Highlight slices of an audio or video file, and mark them with whatever labels you need. You can zoom in and out to make your annotations more precise, and easily start, stop and replay the input to make sure you get it right. Keyboard shortcuts and scriptable automation make sure you'll fly through the task as quickly as possible. Perfect for tasks like speaker diarization, topic segmentation and disfluency elimination.
Read moreTry it live and select regions!
Try it live and select regions!
Try it live and select the category!
Try it live and transcribe the audio!
Classify, summarize or transcribe
Quickly sort audio or video inputs into custom categories, marking them as relevant or irrelevant, or grouping them for further analysis. Add one or more text boxes to transcribe audio or summarize scenes, with simple server-side validation to make sure your data meets whatever consistency and quality standards you require.
Read morePlug in your own models
Custom recipes let you integrate machine learning models using any framework of your choice, load in data from different sources, implement your own storage solution or add other hooks and features. No matter how complex your pipeline is – if you can call it from a Python function, you can use it in Prodigy.
View examplesrecipe.py@prodigy.recipe("custom-audio-recipe")
def custom_audio_recipe(dataset, data_dir):
stream = Audio(data_dir)
model = load_your_model()
return {
"dataset": dataset,
"stream": model(stream),
"update": model.update,
"view_id": "audio_manual"
}