AI Dataset2026
Provides 100 English–Khasi parallel sentence pairs with aligned studio-quality WAV recordings for ASR, TTS and translation evaluation; curated by Medharvix as a restricted public sample—full corpus available by request.
AI Model2026
Multilingual 2B speech–language model for ASR and bidirectional speech translation (EN, FR, DE, ES, PT, JA), providing punctuation/truecasing, keyword biasing, and a dual-head CTC encoder to boost transcription accuracy.
AI Model2026
7B multilingual translation model optimized for instruction-following and low-latency deployment across 33 languages; provides quantized/FP8/GGUF builds and integrations (vLLM, llama.cpp) for server and on-device inference.
AI Model2026
Provides a family of multilingual translation models (1.8B, 7B, 30B-A3B) supporting 33 languages and instruction-following; offers low-bit quantized formats (1.25-bit, 2-bit, FP8, GGUF) and deployment guides for on-device and server inference.
AI Dataset2026
Parallel Chinese→Vietnamese dataset of webnovel (xianxia) text provided in JSON for NMT training and teacher-student distillation. In-domain, ~100K–1M examples with CC-BY-4.0 license — useful for fine-tuning or distillation experiments but limited by narrow genre and small download footprint.
AI Dataset2026
Large streaming-audio dataset for training and evaluating audio-LLMs and audio agents. About 2.28M clips grouped into multi-turn “streams” across six task subsets (ASR, speech translation, audio understanding, voice chat, proactive response, environment-aware); audio shipped as tar shards.
Trains LLMs with reinforcement learning using a surface chrF reward so models learn to extract and apply linguistic signals from rich context for translating completely unseen languages. Demonstrates better zero-shot translation than in-context learning or supervised fine-tuning, framing outcome-based RL as a meta-skill for language learning from context.
AI Dataset2026
Provides over 1.1M hours of high-bandwidth, multichannel multilingual speech with segment- and word-level timestamps, English translations, and per-file metadata for ASR, TTS and audio-representation research. Preserves original 48kHz multichannel OPUS audio and is released under CC BY 3.0.
AI Dataset2026
A living, crowdsourced dataset of hard-to-translate examples (text, images, audio, video) paired with handcrafted verification rules that flag concrete MT failures. LTBv1 contains 3,456 peer-reviewed examples across many language pairs and accepts ongoing contributions.
AI Dataset2026
Provides transcripts, translations, and multi-task text labels for speech across 48 languages and about 463,000 hours. The release contains manifests only; audio must be obtained from the original data providers.
AI Model2026
Translates incoming Chinese or English speech incrementally, aiming to keep lag low without losing meaning. This FP8 checkpoint returns translated text; speech synthesis and voice cloning require a separately configured TTS service.