Restaurant Onsite Call and Reminder Chinese Speech Recognition Audio Dataset
#Speech recognition #natural language processing #speech-to-text #Intelligent customer service #voice assistants #automatic speech recognition
- 500 hours
- 1.6G
- WAV
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In the retail e-commerce industry, with the increasing demand for personalized services and intelligent interaction, improving user experience through speech recognition technology has become a trend. However, existing speech recognition systems perform poorly in noisy restaurant environments, with low accuracy and inability to effectively recognize multiple languages or dialects. This dataset aims to address the challenges of speech recognition in complex dining environments, helping to improve the accuracy of automated systems. Data collection uses professional recording equipment, selecting restaurant scenarios at different times and conditions to ensure coverage of diverse noise backgrounds. Quality control includes multi-round manual annotation and consistency checks, with a team composed of trained language experts and data analysts. Preprocessing steps include noise reduction, audio segmentation, volume leveling, etc., with data categorized by scene and phoneme type stored in WAV format.
Dataset Insights
Sample Examples
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- 295f2b875794a935ae6ba3de4c0c782f.wav00:00
- 886d260f8d094f51b94ee51733c7331a.wav00:00
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_gender | string | The gender of the speaker in the recording. |
| speaker_age_group | string | The age group of the speaker in the recording, e.g., child, teenager, adult, senior. |
| accent | string | The accent of the speaker in the recording, e.g., Standard Mandarin, Cantonese, Beijing Accent, etc. |
| speech_emotion | string | The emotional state expressed by the speaker in the recording, e.g., happy, sad, angry, etc. |
| background_noise_level | string | The level of background noise in the recording such as none, slight, or significant noise. |
| speech_rate | float | The rate of speech by the speaker, expressed in words per minute (WPM). |
| clarity | string | The clarity of the speech in the recording, e.g., very clear, clear, unclear. |
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 application scenarios is this dataset suitable for?
- This dataset is suitable for developing speech recognition applications in the healthcare field, such as automatic reminder systems and emergency call systems.
- Does this dataset include audio in different languages or accents?
- Whether the dataset includes audio in different languages or accents requires checking the dataset's detailed description.
- How can this dataset be used to improve the performance of a speech recognition system?
- The diverse speech samples in this dataset can be used to train models to improve recognition accuracy and robustness.
- What healthcare scenarios are covered by the audio samples in this dataset?
- The audio samples cover common call and reminder scenarios such as medication reminders and health check notifications.
- When using this dataset for research, do privacy issues need to be considered?
- Yes, researchers must adhere to relevant privacy protection and data compliance requirements during use.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Restaurant Onsite Call and Reminder Chinese Speech Recognition Audio Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/9c0f01ef821d67cd860cd4b329d0e87a?cate=1},
urldate={2026-02-04},
keywords={Chinese speech recognition, retail e-commerce speech data, restaurant speech recognition},
version={1.0}
}Using this in research? Please cite us.
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