In the Language Bank: Tuukka Törö

Kielipankki – The Language Bank of Finland offers a comprehensive set of resources, tools and services in a high-performance environment. Tuukka Törö tells us about his research on Finnish speech synthesis. Neural network models enable researchers to analyze speech in new ways.

Who are you?

I am Tuukka Törö. I have been working as a doctoral researcher at the University of Helsinki’s Phonetics and Speech Synthesis Research Group since the beginning of this year. My background is in linguistics and phonetics, and I hold a BA in English studies from the University of Malmö and an MA in Phonetics from the University of Helsinki. After writing my Master’s thesis on controlling speaking styles in speech synthesis, I spent some time working with YLE on AI radio projects where we created synthetic ‘actors’ for radio features.

In my current position, I work in the Academy of Finland funded project . The project’s aim is to develop text-to-speech (TTS) synthesis inspired by the predictive processing theory of human cognition.

While my focus has become more technically inclined, the primary inspiration behind my work stems from a fascination with how social structures influence speech, from macro level variation to how people convey social dynamics in specific contexts.

What is your research topic?

Currently I am researching macro level language variation using neural-network models built for TTS and speech recognition. While the models’ original purpose is in technological applications, they enable us to analyze speech in new ways. As the models are trained with large amounts of audio, they can be used to model ’wild’ data of varying quality on a large scale instead of picking apart specific acoustic features from small, professionally recorded datasets.

Within the academy project, my aim is to tie together sociolinguistic variation with the predictive processing and speech synthesis side of things. Hopefully, in the coming years we will learn something new about how humans perceive social cues in speech and how high-level social predictions can be utilized to improve speech synthesis.

How is your research related to Kielipankki?

I often use corpora from Kielipankki such as ,  (to be available in Kielipankki), and most of all . In order to train speech synthesizers that we control on social variables – such as age, gender, and dialect – we need a large amount of audio data from people with a rich variety of backgrounds. With Finnish being a relatively small language, it is vital to have a concentrated effort for building large datasets like the Donate Speech corpus.

Recent publications

Törö, T., Suni, A. and Šimko, J. (2024). , Proceedings of Speech Prosody 2024, Leiden, Netherlands.

Šimko, J., Törö, T., Vainio M., and Suni, A. (2023). , Proceedings of the 18th International Congress of Phonetic Sciences, Prague, Czech Republic.

Other related work

  • (AI radio drama, Yle, 2023)
  • (AI radio drama, Yle, 2023)

Corpora

The  consortium consists of a group of Finnish universities along with CSC – IT Center for Science and the Institute for the Languages of Finland (Kotus). FIN-CLARIN helps the researchers of Social Sciences and Humanities to use, refine, preserve and share their language resources.  is the collection of services that provides the language materials and tools for the research community.