High-Quality Training Datasets

100 Million Sets of 3D Scene & Object Data contains 60 million sets of real-space scene data, 40 million sets of simulated synthetic scene data, and 100,000 sets of high-quality 3D object assets. The real-space scene data covers a wide range of scenarios including real estate, restaurants, cultural and museum venues, commercial retail, cultural tourism, hospitality, industrial facilities, and commercial offices; the floor plan data of simulated synthetic scenes is derived from real residential homes; high-quality 3D object assets cover seven top-level categories, namely kitchen and bath, lighting, children's furniture, home appliances, furniture, home decor, and hard furnishings, and it includes interactive object models with physical parameters. This dataset can be used for the training of embodied models.

A large-scale, real-world teleoperation dataset for embodied AI manipulation, captured in genuine homes with the portable uDAS 1.0 system. It spans ~50,000 hours of valid footage: ~934,000 episodes (avg. 3.2 min each) covering everyday household activities, and ~19.2 million subtask segments. Each episode synchronously records six first-person video streams — head cameras at 1408 × 1280 and wrist cameras at 640 × 480, all 30 fps H.264 — plus 30 Hz proprioceptive data: bimanual end-effector 6-DoF poses, gripper opening and torso pose. Annotation is two-level (task description + subtask timeline) and three-dimensional (scene / object / action, 8 / 13 / 30 multi-tag categories), so any single dimension can serve as an independent evaluation split. Data is delivered in LeRobot v2.1 format by episode and chunk, ready to load out of the box, directly supporting pre-training, fine-tuning and cross-scenario generalization of vision-language-action (VLA) models.

A multimodal embodied AI dataset totaling 10,000 valid hours, collected with a six-camera Ego head-mounted device, and subjected to multiple rounds of quality inspection, AI preprocessing, and fine-grained manual action segmentation and annotation. It covers 25 categories of real-world business scenarios and outputs multi-sensor data in MCAP format along with task-action labels in multiple languages including Chinese, English, Japanese, and Korean.

French Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

Indonesian Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of modal particles). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

Saudi Arabian Arabic Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

Modern Standard Arabic Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

This dataset contains 1,042 egocentric video segments (approximately 35 seconds each) collected across 34 locations and 6 real-world environments, including homes, offices, and retail scenarios. Powered by self-developed VSLAM system, achieving millimeter-level positioning, multi-sensor hard-triggered synchronization (≤1ms), and a high frame rate of 60fps for RGB. It includes multi-view videos, calibrations, point clouds, SLAM trajectories, and gesture recognition results in standard formats. Designed for embodied AI, spatial perception, and 3D reconstruction, it offers high precision, diverse scenarios, and out-of-the-box usability, making it ideal for training robust perception-action models.

Japanese Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of modal particles). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

Italian Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

Brazilian Portuguese Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.

German Natural Conversational Speech Synthesis Corpus. Recorded by two native voice talents (one male, one female), this corpus comprises two modules: free dialogue on specified topics and scripted emotional/paralinguistic text performances. It covers single-emotion, multi-emotion, and paralinguistic expressions (including a variety of interjections). Professional linguists have provided three-tier annotation—on text content, emotion labels, and paralinguistic phenomena. The total duration is approximately 11 hours, with audio specifications of 48 kHz sampling rate, 24‑bit depth, WAV format, mono channel. This dataset is designed to fully meet the diverse requirements of TTS research and development in terms of naturalness, expressiveness, and precise annotation.