AI Dataset2025
Provides MS MARCO queries, passages and answers translated into 14 Indic languages while keeping the original English content and per-example translation metadata. Includes train/validation splits, passage selection flags, and translation model parameters for multilingual IR, QA and RAG research.
AI Audio2025
Generates and edits full-length music locally using a hybrid language-model planner and a diffusion transformer. Provides text- and audio-driven song synthesis plus selective editing (cover generation, repainting, vocal→BGM), metadata control and lightweight LoRA personalization, and runs on consumer GPUs/CPUs.
AI Dataset2025
Yuhang Dai, Ziyu Zhang +14Audio, Speech and Language Processing Group (ASLP@NPU), Northwestern Polytechnical University, Beijing AISHELL Technology Co., Ltd. +3
Provides a 10,000-hour Sichuanese (Chuan-Yu) speech corpus with rich annotations (timestamps, speaker age/gender/emotion, SNR, DNSMOS) and unified metadata for ASR and TTS research; includes metadata.jsonl, evaluation benchmarks, and an LLM-assisted transcription pipeline.
AI Dataset2025
Provides a reproducible, deduplicated corpus of text extracted from PDFs for LLM pretraining—about 3 trillion tokens from ~475 million documents in 1733 language-script pairs. Includes OCR and text extraction pipelines, per-page language IDs, MinHash deduplication, and is released under ODC‑By 1.0.
AI Dataset2025
Open synthetic corpus for training small reasoning-focused language models — ~79.65M generated samples (≈75B tokens with Pleias tokenizer) amplified from ~58.7k Wikipedia/Wikibooks seeds; includes explicit synthetic reasoning traces, multilingual coverage, and parquet splits.
AI Audio2025
Delivers multilingual, on-device text-to-speech via ONNX Runtime with prebuilt ONNX assets and cross-platform SDKs (Python, Node, mobile); targets low-latency, privacy-preserving TTS with ready demos and 31-language support in v3.
AI Dataset2025
Collects ~200,000 human responses to 20 visual/semantic association questions (e.g., Bouba–Kiki), with per-response image options and demographic metadata — useful for cross‑cultural perception and evaluation of multimodal systems, but not guaranteed as a rigorously controlled experimental sample.
A step-by-step, beginner-first programming course that teaches 'vibe coding'—conversational workflows to turn ideas into AI-enabled web and full‑stack prototypes. Features interactive simulated coding, multi-language docs, stage-based projects (from simple demos to SaaS capstones) and advanced agent/Claude Code guidance.
AI Audio2026
Generates low-latency, streaming text-to-speech entirely on CPUs (no GPU or cloud API required), using an ~100M-parameter model with voice cloning and multilingual support. Optimized for low resource use (2 CPU cores, ~200ms to first audio chunk) — suited for local, privacy-sensitive, or embedded TTS.
AI Dataset2026
Provides open ASR and TTS speech data for 24 Sub‑Saharan African languages to train and evaluate speech models. Includes ~1,250 hours of transcribed ASR and ~235 hours of single‑speaker TTS with train/validation/test/unlabeled splits and mixed CC-BY licenses.
AI Audio2026
Generates controllable multilingual speech from text with nine predefined timbres and custom-voice control; supports voice design, quick voice cloning and low-latency streaming (first audio packet after a single character), suitable for real-time TTS and voice-design workflows.