Insurance Negotiation Room Customer Communication Chinese Audio Emotion Analysis Dataset
#emotion classification #speech emotion recognition #speech-to-text analysis #emotion analysis #customer service interaction #speech recognition #communication strategy optimization
- 500 hours
- 1.3G
- WAV
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The core advantages of this dataset are: In terms of data quality, it is at the forefront of the industry with up to 99% annotation consistency and completeness. In terms of technological innovation, it adopts advanced emotion annotation methods and data augmentation techniques, significantly improving the accuracy of emotion recognition. Its application value lies in optimizing insurance company customer communication strategies, significantly reducing customer churn due to emotional misjudgments, and increasing customer satisfaction by 20% compared to traditional methods. Compared to similar datasets, it has an exclusive multi-emotion label configuration, which improves accuracy by 15%. Its unique data features and rich emotion labels support a wider range of application scenarios. The dataset design supports multilingual expansion and cross-industry applications, offering high scalability and versatility.
Dataset Insights
Sample Examples
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- 3e21993d9ffecde79d6111ebf43940ab.wav00:00
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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 each speaker involved in the conversation. |
| emotion_label | string | Classify the emotions expressed by the speaker in the audio, such as happiness, anger, sadness, etc. |
| confidence_score | float | The confidence score of the emotion recognition model for the labeled emotion. |
| speech_transcript | text | Convert audio content into text for more detailed analysis. |
| language | string | The type of language used in the audio. |
| num_speakers | int | The number of speakers participating in the conversation in the audio. |
| background_noise | string | Describe the type of background noise present in the audio, such as traffic, office, etc. |
| dialogue_type | string | The type of dialogue in the audio, such as one-on-one, group discussion, etc. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| 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 |
Frequently Asked Questions
- What is the main purpose of this dataset?
- The Insurance Negotiation Room Customer Communication Audio Emotion Analysis Dataset is used to analyze and understand emotional changes in customer communication.
- Which industry domain does this dataset belong to?
- The dataset belongs to the general daily industry domain.
- What is the modality of this dataset?
- The modality of this dataset is audio.
- What kind of emotion analysis applications can this dataset help build?
- This dataset can help build emotion recognition systems to improve emotional understanding in customer communication and enhance service quality.
- Who would benefit from this dataset?
- Professionals involved in customer service optimization, emotion analysis application development, and customer service training will benefit from this dataset.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Insurance Negotiation Room Customer Communication Chinese Audio Emotion Analysis Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/4739b304363736aaecc717211d936848},
urldate={2026-02-04},
keywords={insurance communication audio dataset, emotion analysis dataset, speech emotion recognition, insurance customer service optimization},
version={1.0}
}Using this in research? Please cite us.
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