arXiv subjects

Wenke Fan

Publications and source records attributed to Wenke Fan.

3 recordsLinked to original sources

arXiv2026

DuplexDrama: A Synthesized Dialogue Dataset with Scenarios, Full-Duplex Behaviors, Expressive Speech, and Sound Events

We present DuplexDrama, the first synthesized spoken dialogue dataset that simultaneously covers four dimensions: (i) complete persona and scenario settings; (ii) three full-duplex behaviors (interruption, backchannel, incomplete); (iii) expressive speech with persona-aligned emotion labels; and (iv) script-aware sound events. DuplexDrama is built via a 4-stage pipeline; quality validation on both scripts and synthesized audio confirms its quality. We have produced more than 2,000 hours audio data with a 64-voice timbre pool spanning 13 personas and 5 age buckets; 3.8% of all turns carry at least one full-duplex behavior. This data has been validated through internal full-duplex model training. We will release a curated subset of 6,400 bilingual dialogues (800 h, Chinese ~500 h + English ~300 h) to advance full-duplex spoken dialogue model research. Data samples are available at our demo page and LLM-judge evaluation prompts will be released with the dataset.

cs.CL↗

arXiv2026

Same Words, Different Actions: Paired Turn-Taking Evaluation under Rewritten Dialogue Contexts

Real-time spoken dialogue systems must distinguish interruptions that require yielding the floor from backchannels that permit continued speaking. Existing benchmarks typically score events independently and may therefore assign high scores to systems with fixed action preferences rather than context-sensitive decision policies. We introduce ECHO, a paired diagnostic benchmark for Chinese turn-taking evaluation. ECHO pairs examples with the same overlap transcript but contrasting preceding multi-turn dialogue contexts, with one requiring Yield and the other Keep. It additionally includes off-talk examples for diagnosing unnecessary yielding. We introduce pair accuracy, which requires correct decisions on both members of a pair and assigns no credit to constant-action policies. Experiments on four speech systems show that three exhibit a severe over-yielding bias: they correctly keep the floor on fewer than 13% of backchannels, resulting in near-zero pairwise success rates equal or less than 4%. While the remaining system remains comparatively balanced across contexts, these findings broadly demonstrate that interruption-only evaluation can severely overestimate practical turn-taking reliability.

cs.CL↗

arXiv2026

AdaptDuplex: from static to adaptive full-duplex spoken dialogue

Full-duplex spoken dialogue requires simultaneous listening and speaking at sub-second latency, under conversational timing and cognitive demands that change moment to moment. Yet current models mostly impose static operating points, lacking a systematic mechanism for adaptive decisions. We present AdaptDuplex, which upgrades Qwen3-Omni with such a mechanism, co-designed across three layers. A compact token-level protocol represents every window as a canonical sequence, trains dual-stream alignment through a bounded text lead over speech, and exposes every behavioral decision as an explicit token for training-free runtime control via logits bias. Adaptive mechanisms dynamically predict among discrete window durations and augment direct response as needed with non-blocking cognitive consolidation and multi-flight external reasoning. A progressive pipeline introduces these behaviors through a three-stage Thinker curriculum, then Talker-only and joint SFT, with GRPO as a further increment. On Full-Duplex-Bench v1 and v1.5, AdaptDuplex outperforms DuplexOmni and MiniCPM-o 4.5 on the majority of comparable turn-taking, overlap-behavior, and timing metrics, with gains in both interaction decisions and response timing. On the human-recorded HumDial-FDBench, it attains the highest Final score (72.9) of the compared duplex models.

cs.SD↗