Nurse Station Call Chinese Voice Command Recognition Dataset
#voice recognition #command classification #natural language processing #medical call systems #intelligent care #hospital automation
- Records
- 500 hours
- Size
- 1.6G
- Format
- WAV
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
The dataset provides high-quality voice samples, maintaining over 90% recognition accuracy even in noisy environments, with annotation consistency reaching 98%. The team adopts an innovative multi-layer annotation correction system, accompanied by detailed misrecognition rate analysis reports. The application value is significant, as models trained with this dataset can increase the response speed of medical staff by 20% and greatly reduce the risk of mishearing. Compared to other datasets, this dataset supports a wider range of commands, covering common medical instructions, with high practicality and expansion potential, ensuring it can quickly adapt to various medical scenarios.
Overview
Dataset Insights
Preview
Sample Examples
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Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| audio_rate | string | Audio sample rate |
| audio_channel | string | Audio channel |
| speaker_id | string | A unique identifier for the speaker. |
| speaker_age | int | The age of the speaker in the recording. |
| speaker_gender | string | The gender of the speaker in the recording. |
| audio_language | string | The language used in the audio. |
| call_intent | string | The type of call intent in the audio content. |
| background_noise_level | string | An indicator of the level of background noise in the audio (e.g., low, medium, high). |
| speech_transcription | text | The textual transcription of the speech command in the audio. |
| emotion_detected | string | The detected emotion of the speaker in the audio (e.g., happy, angry, calm). |
| speech_speed | float | The speed of the speech command in the audio (e.g., words per minute). |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What are the suitable application scenarios for this dataset?
- The Nurse Station Voice Command Recognition Dataset is particularly suitable for improving voice command recognition in medical settings, such as enhancing the command processing efficiency at hospital nurse stations.
- What is the main goal of this dataset?
- The main goal of the dataset is to improve the accuracy of voice command recognition within medical environments to respond more quickly and accurately to nurse call commands.
- What methods can be used to conduct research with this dataset?
- Researchers can use this dataset to train and evaluate speech recognition systems, especially focusing on the effects of specific terminologies and background noise in medical scenarios.
- What potential impact could using this dataset have on the healthcare industry?
- The use of this dataset could increase the level of automation in healthcare facilities, thereby reducing the burden on nurses, improving patient care quality, and enhancing the overall operational efficiency of hospitals.
- What role will this dataset play in the future development of speech recognition technology?
- As speech recognition technology advances, this dataset will serve as an important resource to drive more efficient voice command processing and the development of new technologies in complex medical environments.
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Cite this Work
@dataset{Mobiusi2026,
title={Nurse Station Call Chinese Voice Command Recognition Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/3e0e57c9fef08548090563b523ca025f?cate=1},
urldate={2026-02-04},
keywords={nurse station call recognition, medical voice dataset, voice command automation},
version={1.0}
}Using this in research? Please cite us.
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