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 Model2026
Open-weights LLM fine-tuned for phone-based voice agents that prioritizes low latency and reliable tool/function calling. Based on NVIDIA Nemotron 3 Nano (30B total, 3.5B active), supports very long contexts (262,144 tokens) and recommends temperature=0 with thinking disabled for deployment.
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 Dataset2026
Provides a dual-channel, channel-separated sample (8.9 hours) and access path to a 1,000‑hour English conversational corpus for commercial and research use. Delivers 48 kHz per-speaker audio, word-level machine transcripts, and per-speaker metadata designed for full‑duplex/turn-taking and ASR/ TTS research.
Provides a realtime audio–language foundation model for fully duplex spoken interaction that listens, interprets acoustic cues, reasons, and speaks in parallel. Key features include Deep Perception for acoustic understanding, Seamless Duplex for synchronized streams, and Think‑While‑Speaking for parallel private reasoning; reports strong benchmark results.
AI Dataset2026
Collection of 1.44M unique Turkish voice‑assistant sentences (≈1,819 hours estimated), normalized for TTS and organized by service domains (appointments, banking, e‑commerce). Designed for training and evaluating TTS and text-generation models; licensed CC BY 4.0 with required attribution.
AI Dataset2026
Provides 3,451 hours (2,051,810 clips) of AI‑generated 48 kHz Turkish speech with transcripts, spoken forms and per‑clip voice descriptions for TTS and ASR development. Includes 2,752 designed voices and is licensed CC BY 4.0 / CC BY‑SA 4.0 (attribution to PatientDesk AI required).
AI Model2026
Converts Turkish text to 48 kHz speech offline using a compact 5.6M DiT acoustic model plus a 3M vocoder (8.6M parameters, ~34 MB). Streams audio with very low latency (~3.86 ms first audio on an RTX 4090), supports fast batching and runs under an Apache‑2.0 license.
AI Audio2026
Generates directed, multi-character, long-form speech from text with natural-language directions and voice cloning. Built on a 35B MoE backbone (3B active per token) with a codebook multi-token-prediction decoder to enable multi-turn revision, infilling edits, streaming, and expressive control.
AI Dataset2026
Provides 525.17 hours of emotionally steered, multilingual speech recordings from 10,420 native speakers across 108 locales for model training and evaluation. Paired series capture neutral/medium/full intensity and varied delivery styles; licensed to permit model training while prohibiting raw-audio redistribution.