AI Audio2026
Generates English speech locally from text into 24 kHz waveforms with a fixed synthetic male voice. Complete text-to-waveform TTS under ~4M parameters (≈16 MB FP32), supports CPU/CUDA inference, deterministic seeds, long-text chunking and an ONNX export path under Apache-2.0 license.
AI Audio2026
Multilingual, real-time ASR for edge CPUs that uses heterogeneous quantization to reduce model size (4.62→1.58 GB) and lower inference latency. Trades some accuracy for 1.6–2.3× faster inference vs. Whisper.cpp and real-time capability on a few CPU threads, making it suitable for memory- and compute-constrained on-device transcription.
AI Audio2026
Multilingual neural text-to-speech model (0.6B params) with zero-shot voice cloning and a bundled 44.1 kHz codec. Preview release targets 11 recommended languages and aims to deliver near-SOTA quality in a compact checkpoint suited for voice cloning and multilingual TTS prototypes.
AI Audio2026
An end-to-end 11B full-duplex speech model for real-time conversational AI that jointly performs streaming speech understanding and generation, enabling ~450 ms turn-taking, barge‑in and live tool calling in a single unified architecture; research use only.
AI Audio2026
Generates complete songs (up to five minutes) from lyrics and a music description, producing 32 kHz stereo WAV with expressive vocals and long-range musical structure. Uses hierarchical LLMs fused with flow-matching/Flow-VAE synthesis for coherent arrangement and timbre; requires CUDA and integrates with Diffusers and SGLang-Omni.
AI Audio2026
Generates and edits speech from natural-language instructions plus optional reference audio, supporting zero-shot TTS, content/acoustic/paralinguistic edits, enhancement, and source separation. Open-source 1.5B-parameter base model with a 4-step distilled AuK‑Flash for faster inference.
AI Audio2026
Zero-shot multilingual text-to-speech checkpoint for speech generation and voice cloning with a compact footprint. Features an ~170M-parameter main model plus a bundled ~120M-parameter codec decoder, with primary support for Chinese and English; other languages show more variable quality and long/noisy references reduce fidelity.
AI Audio2026
Generates low-latency, instruction-driven English and Chinese speech for voice cloning, voice design, and directed performances; supports real-time streaming, reference-free voice creation, and reference-guided cloning. Open-weight PyTorch model released under a research/non-commercial license with GPU recommendations.
AI Dataset2026
Provides 315,000 pairwise human-preference votes comparing 15 English TTS models over 300 operational prompts, with 4,500 high‑quality audio renders and structured vote/pair/prompt records for training or evaluating preference/reward models. Metadata under CC-BY-4.0; audio use governed by model providers' terms.
AI Audio2026
Ruibin Yuan, Hanfeng Lin +56Multimodal Art Projection (MAP), Hong Kong University of Science and Technology (HKUST)
Generates full songs from lyrics and a style prompt, producing vocals and accompaniment and exporting editable symbolic scores for melody/chord control. Uses symbolic planning with agentic multi-turn editing and runs local 48 kHz inference on a 24GB GPU.
AI Audio2026
Provides low-latency, true-streaming automatic speech recognition that emits append-only committed transcripts to avoid partial-result rollbacks. Supports configurable decoding chunks (80 ms–2 s), optimized for Chinese and English, and offers vLLM and transformers backends for real-time deployment.
AI Audio2026
Encodes real audio into YuE2 semantic tokens and ships a matching NAR-branch LoRA so the YuE2 decoder renders realistic latents—enables tokenizing recordings, training artist LoRAs, and generating songs or covers. Includes an 8-layer tokenizer head and a rank-32 decoder LoRA; requires the YuE2 base models and GPU resources.