Speech recognition brings AI to the real world
In the future, artificial intelligence will solve increasingly difficult problems, from designing drugs to improving user interfaces.
Finnish is a tough nut for customer service robots and voice-activated applications to crack.
‘Spoken Finnish differs a great deal from the formal written language,’ explains Mikko Kurimo, professor in speech and language processing at Aalto University. ‘People use different words and shorten and combine them. To manage all that, you need large amounts of spoken language teaching material and new, multilevel algorithms.’
For decades, speech recognition has been an important testbed for AI methods. Deep neural networks are used at different stages of the process. These are machine learning models made up of multiple layers of intercommunicating calculation nodes.
‘Speech recognition is one of those technological applications that have brought AI to the real world,’ Kurimo says. Finnish companies developing language technology already use research done at Aalto in voice-activated customer service robots, TV subtitling, and speech recognition solutions for healthcare.
According to Kurimo, speech recognition research focusing on small languages, such as Finnish, Fenno-Swedish and North Sámi, is important because global tech giants focus mainly on English and other big languages. ‘No one else will develop the best algorithms and technologies for our languages for us, so we have to do it ourselves,’ he says.
Samuel Kaski, professor in computer science at Aalto University and director of the Finnish Centre for Artificial Intelligence (FCAI), adds that research on these small languages may produce universal speech recognition models that are also suitable for the world’s other small languages. ‘As a vital small language, Finnish is therefore a good research subject,’ Kaski says.
An environment that values cutting-edge research
FCAI particularly emphasises the development of intelligent aids based on machine learning solutions that combine mathematical statistics and computer science. AI systems could help humans working to design machines, user interfaces and drug molecules, for example.
One important research subject is combining machine learning with data analysis to ensure that personal information in the source data cannot be identified. ‘This would enable us to use, for example, hospital data in medical research without compromising privacy,’ Kaski says.
FCAI is part of the ELLIS Society, the European Laboratory for Learning and Intelligent Systems, which aims to improve the conditions for AI research in Europe. Kaski points out that, in the interest of national competitiveness, Finland should strive to remain an attractive research environment for AI experts.
‘We have to create an environment that values cutting-edge research,’ he says. We can become a global leader by providing networking opportunities for top researchers.’
Text by Panu Räty