Researchers have taught an algorithm to 'taste'
Incorporating human tastes into artificial intelligence makes it easier for wine buyers thirsting for the right wine. Researchers at the University of Copenhagen’s Pioneer Centre for AI have shown that AI can accurately predict individual wine preferences. The researchers expect that nourishing machines with human sensory experiences will continue to grow.
![](/data/images/public/13561218/13757241/b84d97dd-8a1b-4ee3-ab30-80853530b9c0-w_720.jpg)
For non-connoisseurs, picking out a bottle of wine can be challenging when scanning an array of unfamiliar labels on the shop shelf. What does it taste like? What was the last one I bought that tasted so good?
Here, wine apps like Vivino, Hello Vino, Wine Searcher and a host of others can help. Apps like these let wine buyers scan bottle labels and get information about a particular wine and read the reviews of others. These apps build upon artificially intelligent algorithms.
Now, scientists from the Technical University of Denmark (DTU), the University of Copenhagen and Caltech have shown that you can add a new parameter to the algorithms that makes it easier to find a precise match for your own taste buds: Namely, people's impressions of flavour.
"We have demonstrated that, by feeding an algorithm with data consisting of people's flavour impressions, the algorithm can make more accurate predictions of what kind of wine we individually prefer," says Thoranna Bender, a graduate student at DTU who conducted the study under the auspices of the Pioneer Centre for AI at the University of Copenhagen.
More accurate predictions of people's favourite wines
The researchers held wine tastings during which 256 participants were asked to arrange shot-sized cups of different wines on a piece of A3 paper based upon which wines they thought tasted most similarly. The greater the distance between the cups, the greater the difference in their flavour. The method is widely used in consumer tests. The researchers then digitized the points on the sheets of paper by photographing them.
The data collected from the wine tastings was then combined with hundreds of thousands of wine labels and user reviews provided to the researchers by Vivino, a global wine app and marketplace. Next, the researchers developed an algorithm based on the enormous data set.
"The dimension of flavour that we created in the model provides us with information about which wines are similar in taste and which are not. So, for example, I can stand with my favourite bottle of wine and say: I would like to know which wine is most similar to it in taste – or both in taste and price," says Thoranna Bender.
Professor and co-author Serge Belongie from the Department of Computer Science, who heads the Pioneer Centre for AI at the University of Copenhagen, adds:
"We can see that when the algorithm combines the data from wine labels and reviews with the data from the wine tastings, it makes more accurate predictions of people's wine preferences than when it only uses the traditional types of data in the form of images and text. So, teaching machines to use human sensory experiences results in better algorithms that benefit the user."
Can also be used for beer and coffee
According to Serge Belongie, there is a growing trend in machine learning of using so-called multimodal data, which usually consists of a combination of images, text and sound. Using taste or other sensory inputs as data sources is entirely new. And it has great potential – e.g., in the food sector. Belongie states:
"Understanding taste is a key aspect of food science and essential for achieving healthy, sustainable food production. But the use of AI in this context remains very much in its infancy. This project shows the power of using human-based inputs in artificial intelligence, and I predict that the results will spur more research at the intersection of food science and AI."
Thoranna Bender points out that the researchers’ method can easily be transferred to other types of food and drink as well:
"We’ve chosen wine as a case, but the same method can just as well be applied to beer and coffee. For example, the approach can be used to recommend products and perhaps even food recipes to people. And if we can better understand the taste similarities in food, we can also use it in the healthcare sector to put together meals that meet with the tastes and nutritional needs of patients. It might even be used to develop foods tailored to different taste profiles."
The researchers have published their data on an open server and can be used for free.
"We hope that someone out there will want to build upon our data. I've already fielded requests from people who have additional data that they would like to include in our dataset. I think that's really cool," concludes Thoranna Bender.
![null](https://via.ritzau.dk/data/images/public/13561218/13757241/af3ddf45-16a1-4a74-883c-f667c7fd5700-w_720.jpg)
ABOUT THE STUDY
- The researchers' dataset is available on the project website.
- The research article about the project was recorded at the NeurIPS 2023 conference and is based on Thoranna Bender's thesis, which she wrote while affiliated with the University of Copenhagen’s Pioneer Centre for AI.
- The authors behind the study are: Thoranna Bender, Simon Moe Sørensen, Grethe Hyldig, Søren Hauberg and Frederik Warburg from the Technical University of Denmark (DTU); Alireza Kashani from Vivino; K. Eldjarn Hjørleifsson from the California Institute of Technology (Caltech) and Serge Belongie from the University of Copenhagen.
- The research project was conducted in collaboration with Vivino.
- The research is supported by the Danish Data Science Academy (DDSA) and the Pioneer Centre for AI.
Keywords
Contacts
Thoranna Bender
Master's student
Technical University of Denmark (DTU)
thorannabender@gmail.com
+45 50 23 04 63
Serge Belongie
Professor
Pioneer Centre for AI / Department of Computer Science
University of Copenhagen
sjb@aicentre.dk
+45 93 58 87 86
Maria Hornbek
Journalist
Faculty of Science
University of Copenhagen
maho@science.ku.dk
+45 22 95 42 83
Images
Links
ABOUT THE FACULTY OF SCIENCE
The Faculty of Science at the University of Copenhagen – or SCIENCE – is Denmark's largest science research and education institution.
The Faculty's most important task is to contribute to solving the major challenges facing the rapidly changing world with increased pressure on, among other things, natural resources and significant climate change, both nationally and globally.
Subscribe to releases from Københavns Universitet - Det Natur- og Biovidenskabelige Fakultet
Subscribe to all the latest releases from Københavns Universitet - Det Natur- og Biovidenskabelige Fakultet by registering your e-mail address below. You can unsubscribe at any time.
Latest releases from Københavns Universitet - Det Natur- og Biovidenskabelige Fakultet
Fungus gnat entombed in a 40-million-year-old piece of amber is a rare gem30.8.2024 06:00:00 CEST | Pressemeddelelse
A Danish amber collector’s find upon a wild North Sea shore in the 1960’s has proved to be of great and surprising significance. After having thoroughly examining the roughly 40-million-year-old piece of amber, University of Copenhagen researchers have discovered it to contain the first fossil of a predatory fungus gnat belonging to a rare genus. The research contributes new knowledge about the distribution of the gnat species and about biodiversity across space and time.
Myggeart opdaget i 40 millioner år gammelt rav er en sjælden perle30.8.2024 06:00:00 CEST | Pressemeddelelse
En Vestjysk ravsamler fandt i 1960’erne et unikt myggefossil uden at vide det. Nu har forskere fra Københavns Universitet undersøgt det ca. 40 millioner år gamle rav, som indeholder det første fossil af en rovsvampemyg som tilhører en sjælden slægt. Forskningen bidrager med ny viden om myggeartens udbredelse og fortidens biodiversitet.
Næsten erklæret uddød: Yderst sjælden bi genopdaget efter 50 år26.8.2024 07:00:00 CEST | Pressemeddelelse
Et forskerhold fra Københavns Universitet har genopdaget den udryddelsestruede overdrevsvejbi i Jægerspris på Nordsjælland. Bien er sidst set i Danmark i 1973 og ville om få år være erklæret nationalt uddød. Fundet peger på, at græssende kvæg og heste hele året rundt gavner de vilde bier.
Historisk stor bevilling skal give Danmark verdens bedste naturvidenskabelige undervisere22.8.2024 07:00:00 CEST | Pressemeddelelse
Med forskning i international topklasse og 125 millioner kroner i ryggen fra Novo Nordisk Fonden skal Københavns Universitet sammen med Aarhus og Syddansk Universitet gøre os klogere på, hvordan man leverer den bedste naturvidenskabelige undervisning på universiteterne. Satsningen er den største enkeltstående satsning på globalt plan og bringer Danmark i front på et historisk underprioriteret område.
Widespread practice among athletes harms both performance and health15.7.2024 10:27:00 CEST | Press release
Drastically cutting back on caloric intake to lose weight ahead of competition is commonplace among athletes. However, this type of 'dieting' doesn’t just diminish performances, it can also compromise their immune systems. These are the findings of a new study from the University of Copenhagen.
In our pressroom you can read all our latest releases, find our press contacts, images, documents and other relevant information about us.
Visit our pressroom