Would you like a proper introduction to Cynefin, a framework for making sense of the world and its problems? Or why not a basic cover of speech recognition? Join Women in Data this week for two interesting talks covering Cynefin and Speech Recognition.
Cynefin is a framework for making sense of the world and its problems; for understanding where outcomes are predictable, where they might emerge with experiment and feedback, and where urgent action is required. Applied to any kind of knowledge work, Cynefin can help us to use libraries and services effectively, engage expertise appropriately, develop solutions innovatively, and avoid the pitfalls of disorder and chaos that plague so many projects.
Liz Keogh is a Lean and Agile consultant based in London. She is a well-known blogger and international speaker, a core member of the BDD community and a contributor to a number of open-source projects including JBehave. She specializes in helping people use examples and stories to communicate, build, test and deliver value, particularly when faced with high risk and uncertainty. Liz's work covers topics as diverse as story-writing, haiku poetry, Cynefin and complexity thinking, effective personal feedback and OO development, and she has a particular love of people, language, and choices. She has a strong technical background with over 20 years’ experience in delivering value and coaching others to deliver, from small start-ups to global enterprises. Most of her work now focuses on Lean, Agile and organizational transformations, and the use of transparency, positive language, well-formed outcomes and safe-to-fail experiments in making change innovative, easy and fun.
In this talk I'll cover the basics of speech recognition, and how we use machine learning to model both acoustics of speech and language. I'll talk about some of the things we have to do so that speech recognition works across speakers and languages, and the reasons why speech technology is becoming increasingly popular.
Catherine is a research engineer at Amazon working on speech technology, dialogue, language and machine learning. She holds a PhD in Engineering from Cambridge University, and has since spent time working on speech technology in both industry and academia.