August NH Section ExCom meeting Virtual: https://events.vtools.ieee.org/m/461769

https://us02web.zoom.us/webinar/register/4017283227834/WN_BIVpgswKS_-lgwEIZXEAnQ#/registration Often the stumbling block to getting started with Oracle 23ai Machine Learning (ML) is finding sufficient hardware and software resources. What if you could do that within a Docker container ... in a matter of minutes? Join Abi Giles-Haigh, Oracle ACE Director and Analytics & Innovation Director at Capgemini, as she shows how simple it is to exactly that. And since it's a Oracle 23ai DB, you can rest assured that crucial training data, algorithms, and notebooks are retained securely within your Docker environment while you leverage Python to explore ML feature sets. Presenter: Abigail Giles-Haigh, Analytics & Innovation Director, Capgemini Date: Thursday, August 21, 2025 | 9:00am Pacific / 12:00pm Eastern Virtual: https://events.vtools.ieee.org/m/496819

https://landing.signalprocessingsociety.org/ieee-sps-webinars-27-aug-2025 The intersection of speech and language models offer unique opportunities and challenges. This talk provides a comprehensive walkthrough of speech-language model research from NVIDIA NeMo. We cover several types of models such as attention-encoder-decoder Canary-1B, and LLM-based architectures such as SALM or BESTOW. In particular, we highlight the challenges in training and inference efficiency of such models and propose robust solutions via 2D bucketing and batch size OOMptimizer. Finally, we highlight the difficulty of preserving text-domain capabilities in speech-augmented training and present several possible solutions: EMMeTT, VoiceTextBlender, and Canary-Qwen-2.5B. About the Presenter: Piotr Żelasko received the B.S. and M.Sc. degrees in acoustic engineering, and the Ph.D. in electronic engineering from AGH-University Krakow, Poland in 2013, 2014, and 2019 respectively. He is currently a research scientist at NVIDIA NeMo building multitask and multimodal models and efficient training infrastructure. He held a research scientist position at JHU’s CLSP and developed speech technology at different companies (Techmo, Avaya, Meaning.Team). Dr. Żelasko is a co-author of the next-generation Kaldi toolkit (k2) and the maintainer of Lhotse. Speaker(s): Piotr Zelasko, Agenda: https://landing.signalprocessingsociety.org/ieee-sps-webinars-27-aug-2025 Please register here too and on Vtools too. Virtual: https://events.vtools.ieee.org/m/495161

https://landing.signalprocessingsociety.org/ieee-sps-webinars-27-aug-2025 The intersection of speech and language models offer unique opportunities and challenges. This talk provides a comprehensive walkthrough of speech-language model research from NVIDIA NeMo. We cover several types of models such as attention-encoder-decoder Canary-1B, and LLM-based architectures such as SALM or BESTOW. In particular, we highlight the challenges in training and inference efficiency of such models and propose robust solutions via 2D bucketing and batch size OOMptimizer. Finally, we highlight the difficulty of preserving text-domain capabilities in speech-augmented training and present several possible solutions: EMMeTT, VoiceTextBlender, and Canary-Qwen-2.5B. About the Presenter: Piotr Żelasko received the B.S. and M.Sc. degrees in acoustic engineering, and the Ph.D. in electronic engineering from AGH-University Krakow, Poland in 2013, 2014, and 2019 respectively. He is currently a research scientist at NVIDIA NeMo building multitask and multimodal models and efficient training infrastructure. He held a research scientist position at JHU’s CLSP and developed speech technology at different companies (Techmo, Avaya, Meaning.Team). Dr. Żelasko is a co-author of the next-generation Kaldi toolkit (k2) and the maintainer of Lhotse. Agenda: https://landing.signalprocessingsociety.org/ieee-sps-webinars-27-aug-2025 Please register here too and on Vtools too. Virtual: https://events.vtools.ieee.org/m/495161