Patryk Wainaina
About Patryk Wainaina
Patryk Wainaina is an NLP Data Scientist with a background in Speech and Language Processing and Psychology and Linguistics. He has experience in developing text-to-speech solutions and currently works at Starling Bank, having previously held a position at Amazon.
Work at Starling Bank
Patryk Wainaina has been employed at Starling Bank as an NLP Data Scientist since 2022. In this role, he focuses on machine learning applications specifically tailored for natural language processing (NLP). His work contributes to enhancing the bank's capabilities in handling language-related tasks, particularly in low-resource settings.
Education and Expertise
Patryk Wainaina holds a Master of Science (MSc) in Speech and Language Processing from The University of Edinburgh, where he studied from 2019 to 2020. He also earned a Bachelor of Arts (BA) in Psychology and Linguistics from the University of Oxford, completing his studies there from 2015 to 2019. His academic background provides a strong foundation for his expertise in NLP and machine learning.
Background
Before joining Starling Bank, Patryk Wainaina worked at Amazon as a TTS Language Engineer from 2020 to 2022 in Cambridge, England. During his tenure, he developed text-to-speech (TTS) front-end solutions, focusing on homograph disambiguation and text normalization. He also built and maintained neural engines capable of generating life-like speech in multiple languages, including English, German, and Spanish.
Achievements in Text-to-Speech Technology
Patryk Wainaina has made significant contributions to the field of text-to-speech technology. His work includes developing front-end solutions that enhance the accuracy of speech synthesis through homograph disambiguation and text normalization. Additionally, he has experience in building neural engines that produce natural-sounding speech across various languages, showcasing his technical skills in this area.
Specialization in Machine Learning
Patryk Wainaina specializes in applying machine learning techniques to text-to-speech and natural language processing tasks. His focus on low-resource settings highlights his commitment to developing solutions that are accessible and effective in diverse linguistic environments. This specialization is integral to his current role at Starling Bank and reflects his broader professional interests.