Speech Analysis
Speech analysis is a rapidly evolving field focused on understanding and manipulating spoken language using computational methods, aiming to improve human-computer interaction and address challenges in healthcare and other domains. Current research emphasizes developing robust models, often based on transformer networks and neural codecs, for tasks such as speech recognition, emotion detection, and generation, including handling multi-speaker scenarios and low-resource languages. These advancements have significant implications for applications ranging from improved accessibility for individuals with speech impairments to more natural and intuitive interfaces for various technologies, as well as enabling new diagnostic tools in healthcare.
Papers
Pre-Trained Foundation Model representations to uncover Breathing patterns in Speech
Vikramjit Mitra, Anirban Chatterjee, Ke Zhai, Helen Weng, Ayuko Hill, Nicole Hay, Christopher Webb, Jamie Cheng, Erdrin Azemi
PCQ: Emotion Recognition in Speech via Progressive Channel Querying
Xincheng Wang, Liejun Wang, Yinfeng Yu, Xinxin Jiao
Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual Support
Karn N. Watcharasupat, Chih-Wei Wu, Iroro Orife
Speech After Gender: A Trans-Feminine Perspective on Next Steps for Speech Science and Technology
Robin Netzorg, Alyssa Cote, Sumi Koshin, Klo Vivienne Garoute, Gopala Krishna Anumanchipalli
Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency
Sakib Shahriar, Brady Lund, Nishith Reddy Mannuru, Muhammad Arbab Arshad, Kadhim Hayawi, Ravi Varma Kumar Bevara, Aashrith Mannuru, Laiba Batool
SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Words
Junyi Ao, Yuancheng Wang, Xiaohai Tian, Dekun Chen, Jun Zhang, Lu Lu, Yuxuan Wang, Haizhou Li, Zhizheng Wu
Coding Speech through Vocal Tract Kinematics
Cheol Jun Cho, Peter Wu, Tejas S. Prabhune, Dhruv Agarwal, Gopala K. Anumanchipalli
Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech
Adrien Pupier, Maximin Coavoux, Jérôme Goulian, Benjamin Lecouteux
PSLM: Parallel Generation of Text and Speech with LLMs for Low-Latency Spoken Dialogue Systems
Kentaro Mitsui, Koh Mitsuda, Toshiaki Wakatsuki, Yukiya Hono, Kei Sawada
Exploring Spoken Language Identification Strategies for Automatic Transcription of Multilingual Broadcast and Institutional Speech
Martina Valente, Fabio Brugnara, Giovanni Morrone, Enrico Zovato, Leonardo Badino
LASER: Learning by Aligning Self-supervised Representations of Speech for Improving Content-related Tasks
Amit Meghanani, Thomas Hain