size_categories:1K<n<10K language:en region:us
---
language:
- en
size_categories:
- 1K<n<10K
---
This dataset came from Kaggle and was contributed by Paul Mooney.
https://www.kaggle.com/datasets/paultimothymooney/medical-speech-transcription-and-intent/data

Context
8.5 hours of audio utterances paired with text for common medical symptoms.

Content
This data contains thousands of audio utterances for common medical symptoms like “knee pain” or “headache,” totaling more than 8 hours in aggregate. Each utterance was created by individual human contributors based on a given symptom. These audio snippets can be used to train conversational agents in the medical field.

This Figure Eight dataset was created via a multi-job workflow. The first involved contributors writing text phrases to describe symptoms given. For example, for “headache,” a contributor might write “I need help with my migraines.” Subsequent jobs captured audio utterances for accepted text strings.

Note that some of the labels are incorrect and some of the audio files have poor quality. I would recommend cleaning the dataset before training any machine learning models.

This dataset contains both the audio utterances and corresponding transcriptions.

Acknowledgements
This dataset was developed by figure-eight and can be downloaded from https://www.figure-eight.com/dataset/audio-recording-and-transcription-for-medical-scenarios/ along with instructions on how to make similar datasets using the figure-eight platform.

https://www.figure-eight.com/dataset/audio-recording-and-transcription-for-medical-scenarios/

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