Luan Vin\'icius Fiorio, Alex Young, Ronald M. Aarts, "Hybrid Real- And Complex-Valued Neural Network Concept For Low-Complexity Phase-Aware Speech Enhancement," arxiv.org/abs/2509.21185
Haolin He, Xingjian Du, et al., "Measuring Audio's Impact on Correctness: Audio-Contribution-Aware Post-Training of Large Audio Language Models,", arxiv.org/abs/2509.21060
Monica Sekoyan, Nithin Rao Koluguri, Nune Tadevosyan, Piotr Zelasko, Travis Bartley, Nikolay Karpov, Jagadeesh Balam, Boris Ginsburg, "Canary-1B-v2 & Parakeet-TDT-0.6B-v3: Efficient and High-Performance Models for Multilingual ASR and AST," arxiv.org/abs/2509.14128
Jing-Tong Tzeng, Bo-Hao Su, Ya-Tse Wu, Hsing-Hang Chou, Chi-Chun Lee, "Lessons Learnt: Revisit Key Training Strategies for Effective Speech Emotion Recognition in the Wild," arxiv.org/abs/2508.07282
Riki Shimizu, Richard J. Antonello, Chandan Singh, Nima Mesgarani, "Interpretable Embeddings of Speech Enhance and Explain Brain Encoding Performance of Audio Models," arxiv.org/abs/2507.16080
Sangmin Lee, Woo-Jin Chung, Hong-Goo Kang, "LAMA-UT: Language Agnostic Multilingual ASR through Orthography Unification and Language-Specific Transliteration," arxiv.org/abs/2412.15299
Rostislav Makarov, Lea Sch\"onherr, Timo Gerkmann, "Are Modern Speech Enhancement Systems Vulnerable to Adversarial Attacks?," arxiv.org/abs/2509.21087
Tan Dat Nguyen, Jaehun Kim, Ji-Hoon Kim, Shukjae Choi, Youshin Lim, Joon Son Chung, "SPADE: Structured Pruning and Adaptive Distillation for Efficient LLM-TTS," arxiv.org/abs/2509.20802
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