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【Product Type】Odia language from India, free conversation, mobile 16K 【Corpus Type】 Home, health, travel, education, work, gourmet food, marriage, movies, music, socializing, celebrities, weather, sports, and other common topics in daily life Natural context, applicable to the entire industry 【Pronouncer Information】 Gender: Male 44%, Female 56% Age: Pronouncers mainly cover the age range of 16-45 Accent: Pronouncers are from Odisha state.

Product Features: This dataset has collected 100,000 dance videos, each averaging 30 seconds in length, at 4K resolution, including adults and teenagers with a foundation in dance, with a balanced gender ratio. It includes both solo and group dances, with high richness in videos from various angles such as front, side, back, and turning. Dance types include folk dance, jazz, street dance, and more. Application Fields: This dataset can be applied to virtual humans, VR, dance education, video production, and other fields, promoting the application and development of multimodal technology in the corresponding areas.

This product library is a cabin DMS (Driver Monitoring System) for foreign adult data collection, solely capturing IR (Infrared) videos and images. The DMS captured 700 foreign adults, with 20% Blacks and 80% Whites. The shooting mode is individual, with 25 fixed cameras arranged inside the cabin for synchronized recording, and an additional camera for supporting shots. Props include hats (20%), regular glasses (25%), sunglasses (25%), masks (20%), with their configurations randomly overlapping. The vehicle models are 5-seater passenger cars (consisting of smart, BYD Dolphin, and BYD Song, totaling three vehicles), and the vehicles were stationary during the shooting. The lighting conditions of capturing include frontal lighting, back lighting, side lighting, interior car lighting, streetlights, shade under trees, oncoming headlights, cloudy days, and rainy days. The capturing content consists of both action and gaze, with videos for action capture and images for gaze capture, along with calibration data. The video action capture scenarios are divided into 18 basic scenes and 8 additional scenes, totaling 26 categories. All data include the first 18 basic actions, and some data also include the additional 8 scenes. During the action scene capture, the collectors will simultaneously collect head movements, which are divided into two actions. The collectors randomly perform one of the two actions, with each action accounting for 50% overall. The DMS product library captured approximately 730,000 video segments, with each segment lasting around 30 seconds (700 * 18 * 25 * [lighting conditions]). It also captured approximately 204,554,000 gaze and action images (700 * (11 * 25 * 19 + 19 * 26 * 19) * [lighting conditions]), 700,000 original calibration images (700 * 40 * 25), and another 700,000 calibration output images (700 * 40 * 25), which are stored in the images, detection, and reprojection folders respectively.

This dataset covers multiple scenarios such as banking, healthcare, insurance, sales, telecom, travel. The speakers are gender evenly, and each set of the audio is approximately 0.5 hour.

This dataset is Singaporean English Dialogue, applicable for dual channel for mobile and online calls with sentence segmentation data. It covers Telemarketing Customer Service, Financial Consumption, Common Daily Life Language, Social Hotspots, Travel Shopping, Sports Entertainment, Education Learning, Technology Digital Games, where Telemarketing Customer Service and Financial Consumption account for no less than 30%.

This dataset covers over 30 scenarios including sports, entertainment, health, shopping, pet, education, food, travel, and so on.