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Industry Solutions

Automotive

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Automotive

Magic Data provides high quality training and test data for your AI models in many scenarios of intelligent cockpit and autonomous driving to continuously improve the performance of your AI applications.

With industry Know-How as the key feature, we are embracing this new challenge with you and committed to creating more opportunities in the wave of digitalization, automation, and AI.

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Scenarios

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Navigation

Device wake-up, navigation command recognition, POI recognition

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Device Control in or out of the Vehicle

Car window, A/C, seat, lighting system, vehicle door, windscreen wiper

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Virtual Assistant

Information query, travel arrangement, phone call, entertainment

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DMS

Fatigue detection, distraction detection, poor driver behaviour detection

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OMS

Seat belt reminder, dangerous behavior detection, Reminder for carrying baby in vehicle

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Autonomous Vehicle/Advanced Driving Assistance System

Street view semantic recognition, road markings/traffic signs recognition, anomalous object detection

Challenge

In-vehicle scenario
Limited data of fatigue, distraction, and poor driver behavior
Unable to correctly understand commands and queries
Strong or dim light due to environment and weather changes
Stiff and unnatural response
Limited data of emergency and abnormal scenarios

Annotator® AI-Assisted Annotation Platform

Audio Annotation Text Annotation Image Annotation
  • Navigation - Navigation command annotation
  • Device control in or out of the vehicle - Device command annotation
  • Virtual assistant - Voice assistant command and query annotation
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  • Navigation - Speech command generalization
  • Device control in or out of the vehicle - Speech command generalization
  • Virtual Assistant - Command and query generalization
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  • DMS - Keypoint annotation for facial recognition
  • OMS - In-vehicle bounding box annotation for passenger and object recognition
  • CV - Bounding box annotation for out of the vehicle entity annotation, street view semantic segmentation annotation
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MD Dataset Portfolio

Speech Recognition
Text-to-Speech
Natural Language Understanding
OCR

Contact us for data collection and annotation service

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Related Datasets

MDT-BE010 Mandarin Chinese Speech Corpus for TTS

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MDT-AF065 Shanghai Dialect Conversational Speech Corpus

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MDT-RI001 Chinese Spoken Speech Dataset

This dataset is designed to train AI models for better spoken language understanding, enhancing natural interaction in Chinese speech recognition. It features real-world conversations across diverse scenarios, recorded by a wide range of speakers, with high transcription accuracy. All utterances retain full prosodic characteristics of spoken Chinese, with detailed pause and punctuation annotations to help models learn natural rhythm and improve interaction fluency.

MDT-NF018 Shanghai Text Corpus

MDT-AJ039 Japanese Duplex Conversation Training Dataset

This dataset uses high-fidelity independent audio tracks to comprehensively capture natural interaction features in daily conversations, such as interruptions, overlapping speech, intonation shifts, and emotional pauses. All conversations are annotated with multi-speaker labels and span diverse scenarios, providing robust training resources for AI models to comprehend the intricate Japanese honorific system, colloquial ellipses, and context-dependent logic.

MDT-AG022 Chinese Duplex Conversation Training Dataset

Magic Data has proactively launched the "Multi-stream Spontaneous Conversation Training Datasets_Chinese" . This dataset comprises 10,000 hours of Chinese conversational data, encompassing diverse voice scenarios.Our dataset allows AI models to better understand contextual changes, tonal variations, and emotional shifts in conversations, thereby producing responses that are more natural and accurate.
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