NOPE-HYPE is a structured training workflow that integrates a controllable environment simulator, a coverage‑optimal reduction of Power Spectral Density templates, and a concise hyperparameter search over simulator settings. The authors demonstrate that noise generated by the simulator can match the performance of balanced real‑noise training for Whisper and SeamlessM4T models. They also provide principled environment prototype sets and practical default simulator configurations derived from a 27‑run hyperparameter sweep.
By Niramay M. Patel, Bibek Behera, Raksha Sharma
Simulstream is an open‑source toolkit designed to evaluate and demonstrate streaming speech‑to‑text translation systems. It supports both incremental and re‑translation decoding on long‑form speech, offers fine‑grained logging for quality and latency metrics, and includes an interactive web interface for real‑time visualization and comparison. The toolkit addresses the fragmented evaluation landscape by providing a unified framework that accommodates different decoding strategies and input formats.
By Marco Gaido, Sara Papi, Mauro Cettolo, Matteo Negri, Luisa Bentivogli
Conversational ASR for lower-resource languages and niche domains is limited by the scarcity of domain-matched multi-speaker training data. We propose an augmentation pipeline that generates scenario-level dialogues with participant metadata, maps speaker attributes to TTS voice profiles, and assembles synthesized utterances into speaker-aware simulated conversations.
arXiv:2606. 03957v1 Announce Type: cross Abstract: Conversational ASR for lower-resource languages and niche domains is limited by the scarcity of domain-matched multi-speaker training data.
By M\'at\'e Gedeon, P\'eter Mihajlik
arXiv:2607. 02119v1 Announce Type: cross Abstract: While Large Multimodal Models excel in comprehension, high-throughput inference engines lack native support for multimodal generation.
By Haoran Wang, Jinchuan Tian, Siddhant Arora, Shinji Watanabe
arXiv:2605.13841v3 Announce Type: replace-cross
Abstract: Voice agents are increasingly deployed across enterprise applications. However, no existing benchmark jointly addresses realistic conversatio...
By Tara Bogavelli, Gabrielle Gauthier Melan\c{c}on, Katrina Stankiewicz, Oluwanifemi Bamgbose, Fanny Riols, Hoang H. Nguyen, Raghav Mehndiratta, Lindsay Devon Brin, Joseph Marinier, Hari Subramani, Anil Madamala, Sridhar Krishna Nemala, Srinivas Sunkara
arXiv:2606. 09048v1 Announce Type: cross Abstract: Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling.
By Wei Fan, Chao-Hong Tan, Qian Chen, Wen Wang, Xiangang Li, Kejiang Chen, Weiming Zhang, Nenghai Yu
arXiv:2603.16783v2 Announce Type: replace
Abstract: Robust voice agents require exposure to the full diversity of how people interact through speech. However, obtaining enough spoken interactions is...
By Jonggeun Lee, Junseong Pyo, Jeongmin Park, Yohan Jo
arXiv:2606. 19325v1 Announce Type: cross Abstract: Existing multi-speaker dialogue systems bind speakers to utterances through structured supervision: per-turn tags, multi-stream transcriptions, or learnable speaker embeddings.
By Michael Finkelson, Daniel Segal, Eitan Richardson, Shahar Armon, Nani Goldring, Poriya Panet, Nir Zabari, Benjamin Brazowski, Or Patashnik, Yoav HaCohen
arXiv:2606. 13121v1 Announce Type: cross Abstract: Simultaneous speech-to-speech translation aims to enable near-real-time communication by minimizing latency, offering a compelling, real-time alternative to the high latency of consecutive translation.
By Dongwook Lee, Youngho Cho, Sangkwon Park, Heeseung Kim, Sungroh Yoon
arXiv:2605.29948v3 Announce Type: replace-cross
Abstract: Unified speech foundation models require a holistic tokenization space that is both learnable by language models and decodable into high-qual...
By Bohan Li, Shi Lian, Hankun Wang, Yiwei Guo, Yu Xi, Zhihan Li, Da Zheng, Colin Zhang, Kai Yu
arXiv:2606. 07080v1 Announce Type: cross Abstract: We present dots.
By Shi Lian, Changtao Li, Bohan Li, Hankun Wang, Da Zheng, Junfeng Tian, Yufeng Ma, Colin Zhang, Kai Yu