Author Archives: Katrin Affolter

Speech to Text

How a machine tries to understand a dictation Remember in school when you needed to take a dictation? I do, because I was horrible at it! First you needed to understand what the teacher was saying, and then you needed … Read More

Natural Language Interface for Databases

How to get your data without technical knowledge In this time of digitalization, it is quite safe to say that every company has some type of database. It could be a small database to store some contact information, or big … Read More

Machine Translation

Why it is important to have a customized solution In the time of globalization, translations are getting more and more important. Just think about webpages of companies for a moment. Imagine you have a company located in Germany. The corresponding … Read More

From back pain to computer issues

Fun with Language Working with natural language can be challenging and frustrating, but it can be a lot of fun too. Let me share my newest “fun with language” moment: Research is often done in English, and there are many … Read More

Can you come up with another one?

Did you ever wonder why computational linguists always say “natural language is ambiguous and various,” as though that is an explanation why their tasks are complicated? I mean, I get it: There are many different languages and they have different … Read More

“A small change for a word, but a big change for the lemmatizer”

In my previous blogs, I talked about the difficulty provided by natural language (e.g. ambiguity and variety) and the medical domain (e.g. medical words unknown in common tools). Today, I want to show you another aspect: How big the impact … Read More

Can you shorten everything?

Remember my blog post about how in German you can string words together to form new ones? As mentioned in that post, this increases the possible terms for pathologies and can be frustrating when trying to find all possible variations of … Read More

“The more the merrier!”

This idiom describes pretty accurately how we data scientists feel about the data for our machine learning tasks. Generally speaking, the more data we have during training to put through the machine learning models, the better they get. For our … Read More