Benchmarking speech-to-text robustness in noisy emergency medical dialogues: An evaluation of stt-models under realistic acoustic conditions

This dataset provides a representative JSON file containing 99 fully
synthetic German emergency medical service (EMS) dialogue texts used as
ground-truth material in our benchmarking study on speech-to-text (STT)
robustness. Each dialogue represents a prehospital scenario with
conversational exchanges between EMS personnel and patients, and includes
synthetic clinical information (e.g., diagnoses, medications, and vital
signs). In the associated study, these texts served as the basis for
generating synthetic audio samples with text-to-speech systems and for
evaluating multiple STT models under controlled noise conditions. Only the
underlying dialogue texts are included here, as they form the necessary
foundation for reproducing the audio corpus or for conducting related
benchmarking tasks. All contents are fully synthetic, contain no personal
or sensitive information, and may be used freely for research and
methodological development.