Dr Anton Ragni

About

Dr Anton Ragni is a Senior Lecturer in Speech and Language Processing in the School of Computer Science at the University of Sheffield.He graduated with BEng and MEng degrees in Information Technology from the University of Tartu, Estonia, in 2005 and 2007 respectively. He was awarded his PhD from the University of Cambridge in 2013.From 2005 to 2008, he underwent graduate training at the Nordic Graduate School of Language Technology and from 2007 to 2008, he was an intern in the Speech Technology Group, Toshiba Research Europe Ltd, UK. From 2013 to 2018 and from 2018 to 2019, he was a Research Associate and Senior Research Associate, respectively, in Speech Processing at the University of Cambridge.His current research interest focuses on machine learning approaches for speech and languag

Selected publications

• Young S, Evermann G, Gales M, Hain T, Kershaw D, Xunying L, Moore G, Odell J, Ollason D, Povey D , Ragni A et al () The HTK Book (for HTK Version 3.5, documentation alpha version). Cambridge University Engineering Department: Cambridge University Engineering Department.
• Flynn R & Ragni A (2026) Beyond the Utterance: An Empirical Study of Very Long Context Speech Recognition. IEEE Transactions on Audio, Speech and Language Processing, 1-11.
• Zhao M & Ragni A (2026) Decoding Order Matters in Autoregressive Speech Synthesis.. CoRR, abs/2601.08450.
• Mogridge R & Ragni A (2026) Minerva 2 for speech and language tasks. Computer Speech & Language, 95. View this article in WRRO
• Tan X, Zhao M, Cross M & Ragni A (2025) Discrete-time diffusion-like models for speech synthesis.. CoRR, abs/2509.18470.
• Sun W, Tu Z & Ragni A (2024) Energy-based models for speech synthesis. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 12667-12671. View this article in WRRO
• Ma Y, Øland A, Ragni A, Sette BMD, Saitis C, Donahue C, Lin C, Plachouras C, Benetos E, Quinton E , Shatri E et al (2024) Foundation Models for Music: A Survey.. CoRR, abs/2408.14340.
• Cross M & Ragni A (2024) What happens to diffusion model likelihood when your model is conditional?. Proceedings of Machine Learning Research, 255, 1-14. View this article in WRRO
• Ragni A, Gales MJF, Rose O, Knill KM, Kastanos A, Li Q & Ness PM (2022) Increasing Context for Estimating Confidence Scores in Automatic Speech Recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 30, 1319-1329.
• Wang Z & Ragni A (2021) Approximate Fixed-Points in Recurrent Neural Networks.