Natural Language Processing
If any of the following applies to you, you are in the right place:
- As a researcher, do you want to base your empirical findings on linguistic data such as text collections or voice recordings?
- Does your team need help in collecting, managing, processing, or visualising linguistic data?
- Do you want to automate tedious manual tasks?
- Do you intend to make your documents machine-readable?
- Do you want to detect historical trends, political leanings, and personal stance in natural language data?
- Do you have an interesting application in mind which is built on text, audio recordings or eye-tracking data?
- Do you want to use semantic analysis methods like collocations, word embeddings and Neural Networks?
- Do you want to get started implementing language technology solutions yourself?
- Do you have historical documents that you are looking to digitize?
If you need help with the technological side of things, we are here for you!
The Language Technology group consists of experts who support your text and voice technology needs.
- Text Analytics & Data Mining
- Content Analysis
- Information Retrieval & Extraction
- Part-of-speech tagging, syntactic parsing, semantic tagging
- Sentiment Detection
- Creation and adaption of language models
- Data Classification
- Machine Learning (including Neural Networks & Deep Learning)
- Machine Translation
- Statistical Data Processing
- Audio signal processing (e.g. for human speech or animal vocalizations)
- Speech Recognition and Synthesis
- Data conversion
We offer consulting, coaching, and support in the following scenarios (among others):
- Digitization of printed texts and manuscripts (including OCR)
- Efficient information extraction and analysis of large text collections
- Enrichment of texts with named entities, sentiment analysis, topic modeling, and classification, including multilingual and historical documents
- Advice on tools, software, and best practices
- Help with project applications and common projects
Teasers from our Research
Coaching and Teaching
Example from a Worskshop, teaching Content Analysis with R
Semantic Analysis
Example of a Result: Conceptual Map of Associations to Wine, Cider and Beer
Stylistics
Characterisation of the Language of Donald Trump
https://www.blick.ch/news/linguistik-trumps-sprache-einfach-sprunghaft-und-emotional-id16163332.html
Examples of our work
Speech-to-text backend for virtual telephone switchboard
