Paper: arXiv:2610.02638 · Code: github.com/adventists-ai/duplexjev · Plugins: pipecat-duplexjev, livekit-plugins-duplexjev The 4B DuplexJev tuned for live end-of-turn: is the user done, right after they go quiet? A turn-taking variant of DuplexJev-4B-Para v1.1, which stays the general 4B. Same recipe as DuplexJev-32B-Para v1.2: the 4B-Para v1.1 mix plus accent data and pause-level turn-taking data, one rank-16 LoRA, 4,000 steps, merged. Qwen3-ASR-0.6B encoder + connector + Qwen3-4B, 4.2 B parameters, bf16, ~10 GB GPU memory. Which 4B to pick. - This one for a voice agent's end-of-turn on a small GPU (LiveKit / Pipecat plugins). - 4B-Para for everything else (stress, non-verbal sounds…
Open weights
cc-by-nc-4.0
4.2B parameters
40,960 tokens
vllm
Sori-1B-MCQ — sori (소리) is Korean for sound — listens to a clip and answers typed questions about it: which of these options, how far along this scale, is this true. It returns the answer, a probability for every option you defined, and a confidence — never prose, never a token stream to parse. Code stays in charge: your program defines the options, reads the numbers and decides what to do. It is the decision model of the Sori Agent project at the Human Interface Lab, Seoul National University. Inspired by TypeSafe's System One model, Jev. Jev showed what a model built for software rather than for conversation looks like: a state, typed questions, calibrated probabilities, one call for many…
Access requested at publisher
other
1.1B parameters
transformers
MOSS-Transcribe-Diarize 0.9B is an end-to-end audio understanding model for long-form multi-speaker transcription, diarization, timestamps, and acoustic event awareness. It supports transcription and diarization across 50+ languages, single-pass inference on audio recordings up to 90 minutes long, and custom hotword prompting for domain-specific terms. Given an audio or video file, the model generates a compact speaker-aware transcript in one pass, including timestamps and anonymous speaker labels such as [S01], [S02], and beyond. 2026-07-22: The subtitle Web UI now supports both Simplified Chinese and English. 2026-07-14: MOSS-Transcribe-Diarize won first place in the 2nd MLC-SLM Challenge…
Open weights
apache-2.0
909M parameters
131,072 tokens
transformers
Model · Audio text to text
Qwen
Qwen2-Audio is the new series of Qwen large audio-language models. Qwen2-Audio is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructions. We introduce two distinct audio interaction modes: We release Qwen2-Audio-7B and Qwen2-Audio-7B-Instruct, which are pretrained model and chat model respectively. For more details, please refer to our Blog, GitHub, and Report. The code of Qwen2-Audio has been in the latest Hugging face transformers and we advise you to build from source with command pip install git+https://github.com/huggingface/transformers, or you might encounter the following error: In the following…
Open weights
apache-2.0
8.4B parameters
8,192 tokens
transformers
strixAE is an audio-language reasoning agent obtained by applying Group Relative Policy Optimization (GRPO) to Audio-Reasoner and merging the trained weights into a standalone checkpoint. It uses the Qwen2AudioForConditionalGeneration architecture and is intended for audio understanding, structured reasoning, and audio-restoration pipeline decisions. The model is designed for research involving: - audio understanding across speech, music, and environmental sounds; - audio-quality and degradation analysis; - deciding whether candidate restoration operations should be applied or skipped; - selecting and ordering an audio-restoration pipeline; - structured audio reasoning and question…
Open weights
mit
8.4B parameters
8,192 tokens
transformers
A small DuplexJev connector: the Whisper-small encoder (frozen) feeds a frozen Qwen3-4B-2507, and every typed question is read as a single-token distribution over its options, with zero decode steps and many questions per forward pass. Trained with the same recipe as the Qwen3-32B connectors released with the paper. Leaderboard scores (see the GitHub README): main language (mean of qa100, ZJU-ML, Easy-Turn) 53.5, paralinguistics (mean of gender, emotion) 43.0. Paper protocol: the evaluation prompts of the paper (single option order, one H200). duplexjev defaults: the package's own prompts with lang matched to the clip. Spoken QA with a small LLM is bounded by the LLM itself (see the…
Open weights
apache-2.0
30M parameters
transformers
