AI Audio2026
Generates expressive, scene-aware speech from XML-style prompts and supports zero-shot voice cloning from 10–20s references. Produces emotional acting, ambient SFX, multilingual output, and continuous long-form narration; requires large model weights and gated Gemma text-encoder access.
AI Model2026
Unified omnimodal foundation model for text, image, video and audio understanding and agentic workflows, with support for up to 1M-token context. Combines a sparse MoE LLM backbone, dedicated vision/audio encoders, multi-token prediction, and a hybrid sliding-window + global attention design to reduce KV-cache overhead.
AI Model2026
Provides a GGUF-quantized build of NVIDIA's Nemotron 3 Nano Omni 30B (Reasoning) for local inference — enables multimodal (video/audio/image/text) reasoning, transcription, and document understanding on compatible runtimes such as llama.cpp, Ollama, vLLM, and TensorRT-LLM.
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 Audio2026
Converts text into natural-sounding speech locally using compact ONNX TTS assets. Optimized for CPU/edge inference (~99M params) with support for 31 languages, expression tags (e.g., <laugh>), and improved stability versus Supertonic 2 — suitable for on-device multilingual TTS.
AI Dataset2026
Provides tick-aligned Counter-Strike 2 player POV video clips with per-tick inputs and world-state sidecars — near-lossless 1280×720@32fps video, per-player stereo audio, and parquet indexes for event/kill/round filtering; suited for RL, video classification and clip mining.
AI Audio2026
Generates high-quality Japanese speech from text with zero-shot voice cloning and emoji-based style controls; uses a flow-matching diffusion transformer over DACVAE continuous latents, includes a duration predictor and integrated SilentCipher watermarking. Japanese-only.
AI Audio2026
Generates music, sound effects, and general audio from text prompts using a medium-size Stable Audio 3 diffusion model — a balance of generation quality and inference cost suitable for prototyping, demo assets, and creative sound design workflows.
AI Dataset2026
Provides a large-scale ASR corpus organized by normalized acoustic subsets for robustness training and evaluation. About 645,925 examples across 54 acoustic conditions (noise, echo, far-field, recording distortions) with many distortion/dropout/noise Parquet splits. Distributed as split Parquet files; license not specified on the dataset page.
AI Audio2026
Converts long-form multi-speaker audio/video into a compact, speaker-aware transcript with timestamps and anonymous speaker labels in one pass. Combines ASR and diarization in a single model, supports custom prompts/hotwords, and targets meetings, podcasts, interviews and long recordings.
AI Model2026
Generates conversational speech and voice continuation from text and optional audio context, outputting Mimi audio codes. Built on a Sesame-style CSM with an 8B Llama-like backbone plus a smaller autoregressive audio decoder. Suited for local TTS inference and voice-cloning workflows.
AI Video2026
Generates audio-driven avatar videos from text, images, or audio inputs with production-grade stability (accurate lip sync, identity consistency) and an 8-step distillation inference mode for faster serving; suitable for broadcasting, virtual hosts, animation, and multi-person scenarios.