Welcome to the Statistical Natural Language Processing Group at the Institute for Computational Linguistics at Heidelberg University. Our research is on the intersection of machine learning and natural language processing, with a special focus on interactive statistical learning techniques. For example, we work on interactive neural machine translation and neural question answering systems, where an artificial intelligence agent learns from human reinforcement/bandit feedback.

We organize the weekly Statistical NLP Colloquium.

group photo
StatNLP group @ Botanical Gardens (next to our department)

Latest news

New publication at EMNLP 2022 Demo Track

JoeyS2T will be presented at the demo track in EMNLP 2022. The paper is available on arxiv. We released pre-trained models for the LibriSpeech ASR and MuST-C en-de Speech Translation benchmarks here.

New publication at MLHC 2022

New research from the StatNLP group on Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis appears at the 6th Machine Learning for Healthcare Conference 2022. The paper is available here.

Tutorial on Statistical Methods for Reproducible Machine Learning at ICML and ECML

Stefan Riezler and Michael Hagmann are invited to present a tutorial on Statistical Methods for Reproducible Machine Learning at leading machine learning conferences: ICML and ECML.

New publications at ACL 2022

Two papers from the StatNLP group are accepted at ACL 2022:


  • “Sample, Translate, Recombine: Leveraging Audio Alignments for Data Augmentation in End-to-end Speech Translation” (arxiv)
  • “Analyzing Generalization of Vision and Language Navigation to Unseen Outdoor Areas” (arxiv)
Monograph "Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science" published

The monograph is published in the Synthesis Lectures on Human Language Technologies series by Morgan & Claypool Publishers.More info