A Harness for Synthesizing Diverse Naturalistic Full-Duplex Conversations

arXiv:2609.28806 · eess.AS, cs.AI · Submitted 2026-09-23 · Read on arXiv

eess.AS, cs.AI

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Core — 11× in this paper · explained in 2 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Accuracy — 8× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Embeddings — 4× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Lexical Diversity — 1× in this paper · explained in 2 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Related papers

• X-VC: Zero-shot Streaming Voice Conversion in Codec Space
• Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers
• Anonymization, Not Elimination: Utility-Preserved Speech Anonymization
• Towards Audio Token Compression in Large Audio Language Models
• WaveScat: Wavelet Scattering Front-Ends with Self-Supervised Features for Speech Deepfake Detection
• ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions