The Flow has not summarised this story yet — read it at arXiv Computation and Language.
ECHO is a new paired diagnostic benchmark designed for Chinese full‑duplex spoken dialogue systems to evaluate context‑sensitive turn‑taking. It pairs examples that share the same overlap transcript but differ in preceding multi‑turn context, requiring either a Yield or Keep decision, and also includes off‑talk cases to test unnecessary yielding. The benchmark introduces pair accuracy, penalizing constant‑action policies, and shows that many systems are biased toward Yield, performing better on interruptions than on backchannels.
DuplexDrama is a newly announced synthesized spoken dialogue dataset that uniquely combines complete persona and scenario settings, three full‑duplex behaviors (interruption, backchannel, incomplete), expressive speech with persona‑aligned emotion labels, and script‑aware sound events. The dataset was created through a four‑stage pipeline and validated for quality on both scripts and audio, yielding over 2,000 hours of audio featuring 64 voices across 13 personas and 5 age groups, with 3.8% of turns containing full‑duplex behaviors. A curated bilingual subset of 6,400 dialogues (800 hours total) will be released to support research in full‑duplex spoken dialogue models, and evaluation prompts will accompany the dataset.
arXiv:2608.28630v1 Announce Type: cross Abstract: Compared with half-duplex dialogue systems where the system waits for user turn completion before it responds, natural full-duplex dialogue systems r...
arXiv:2609.21967v1 Announce Type: cross Abstract: We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combine...
arXiv:2606. 07547v1 Announce Type: cross Abstract: Speech-based large language models are typically constrained to spoken replies, which limits their user-facing outputs to what can be verbalized and suppresses text-native capabilities such as code generation, structured analysis, and multi-step reasoning in realtime interaction, for tasks that require persistent, structured, and inspectable intermediate outputs.
arXiv:2609.36903v1 Announce Type: cross Abstract: End-to-end full-duplex speech models have brought open-source machine conversation closer to human-like interaction, yet existing systems remain limi...