Ekaterina Egorova is a Text-to-Speech Research Lead with nine years of experience bridging academic speech science and industry ML engineering. She earned a PhD focused on OOV detection and recovery and has built hybrid and end-to-end ASR/TTS systems using Kaldi, HuggingFace, Speechbrain and espnet, training competitive models for under-resourced languages. At Brno University of Technology she led multilingual ASR efforts in EU projects and later moved to Seznam.cz where she curated data and trained semantic and TTS models to improve search and voice pipelines. Known for combining linguistic insight with practical ML engineering, she has presented in top conferences and coordinated multi-partner research deliveries. Fluent in both research and project leadership, she now directs TTS research at ValkaAI, applying her background in pronunciation modeling and unsupervised methods to production-ready voice systems.
9 years of coding experience
14 years of employment as a software developer
Bachelor’s Degree, Applied, Experimental and Mathematical Linguistics, with honors, Bachelor’s Degree, Applied, Experimental and Mathematical Linguistics, with honors at Saint Petersburg State University
Doctor of Philosophy (Ph.D.), Information Technology, Doctor of Philosophy (Ph.D.), Information Technology at Brno University of Technology
English, Russian, Czech, Spanish, German, Arabic, French
Contributions:114 pushes, 13 branches in 1 year 4 months
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Ekaterina Egorova - Text-to-Speech Research Lead at ValkaAI