DOI: 10.5061/dryad.gtht76j1b
title: Benchmarking speech-to-text robustness in noisy emergency medical dialogues: An evaluation of stt-models under realistic acoustic conditions

description: 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.
description: # Benchmarking speech-to-text robustness in noisy emergency medical
 dialogues: An evaluation of stt-models under realistic acoustic conditions
 Dataset DOI:
 [10.5061/dryad.gtht76j1b](https://doi.org/10.5061/dryad.gtht76j1b) ##
 Description of the data and file structure ### **1. Overview** This
 dataset contains **99 fully synthetic German emergency medical service
 (EMS) dialogues**, provided in: `synthetic_dialogs.json` Each entry
 represents one complete text-based EMS dialogue simulating a prehospital
 scenario involving interactions between EMS personnel and patients. These
 dialogues served as the ground-truth basis for audio synthesis and
 speech-to-text (STT) evaluation in our study. --- ### **2. How the
 dialogues were generated** All dialogues were originally created for
 research purposes as part of an earlier study (Moser, Bender &
 Sariyar, 2025; DOI:
 [https://doi.org/10.1080/08839514.2025.2519169](https://doi.org/10.1080/08839514.2025.2519169)). The generation process consisted of the following steps: #### **Step 1 — Synthetic EMS case construction** * Structured EMS attributes (e.g., diagnosis, medications, vital signs) were derived from **MIMIC-IV EMS data**. * Using an adapted **Post-Randomization Method (PRAM)**, all structured fields were randomized or swapped to generate **fully synthetic case descriptions**, ensuring that no original MIMIC-IV patient values were retained. #### **Step 2 — Prompt-based dialogue generation** * The synthetic case attributes were inserted into prompt templates. * Large-language models (local and OpenAI API-based variants) were instructed to generate coherent German EMS operation dialogues based on these synthetic case descriptions. --- ### **3. Dialogue structure** Each dialogue represents a continuous EMS operation narrative covering following phases: 1. Arrival on scene and initial patient contact 2. Triage and early vital-sign assessment 3. Medication administration and follow-up assessment Within these dialogues, elements such as **diagnoses, vital-sign measurements, and administered medications** are included as part of the synthetic clinical context. In the JSON file, these phases are combined into a single continuous text for each dialogue. --- ### **4. Data format** The dataset is provided as a single JSON array with 99 entries. Each entry has the following structure: ``` {"convoID": "30394981", ``` ``` "srcText": "Michael Bauer: \"Julia, wir haben einen 45-jährigen Mann mit Übelkeit,..."} ``` \- `convoID` uniquely identifies the dialogue. \- `srcText` contains the **full, continuous synthetic EMS dialogue**. --- ### **5. Relation to earlier work** The methodological foundations of the dialogue-generation pipeline are described in: **Moser D, Bender M, Sariyar M. (2025).** *A pipeline for automating emergency medicine documentation using LLMs with retrieval-augmented text generation.* Applied Artificial Intelligence. DOI: [https://doi.org/10.1080/08839514.2025.2519169](https://doi.org/10.1080/08839514.2025.2519169) --- ### **6. Reproducibility** Audio synthesis and STT evaluation can be reproduced using the generation code available at: **[https://github.com/denMo24/stt-emergency-benchmark](https://github.com/denMo24/stt-emergency-benchmark)** (This external repository is not part of the Dryad submission.)