Helmut Schmid
Helmut Schmid works in computational linguistics, on the tools that assign linguistic structure to text: part-of-speech tagging, morphological analysis and syntactic parsing. The papers here keep returning to one problem, which is scale. They deal with tagsets containing hundreds of fine-grained labels, with grammars extracted from treebanks that allow vast numbers of analyses, and with word formation that produces open-ended vocabularies. The methods combine probabilistic estimation, finite-state transducers and data structures designed for speed. German is the main test language, and Czech appears as well.
The most cited of these papers is Estimation of Conditional Probabilities With Decision Trees. It handles HMM tagging with very large tagsets by predicting each feature of a composite tag one after another, and it lets decision trees select the relevant context attributes in place of a hand-designed backoff order. SMOR describes a finite-state analyser for German that treats inflection, derivation and compounding in a single system. In it, affixes are stored as lexicon entries whose features limit the bases they may attach to. The BitPar paper presents a CKY-style parser that keeps its chart as bit arrays and joins constituents with bitwise operations. This makes heavily ambiguous treebank grammars tractable, even when every analysis is wanted rather than only the best one.
The newest paper here, from 2008, is the decision-tree tagging study. It carries the earlier interest in rich German morphology into statistical tagging, treating morphological features as the internal structure of each tag. The two 2004 papers on morphology and syntax and grammar formalisms came before it. Together the three papers span the main topics of the work, alongside part-of-speech tagging.
Schmid is based at Ludwig-Maximilians-Universität München. Recent bylines also name the Munich Center for Machine Learning and Technische Universität Darmstadt. Earlier papers came from the University of Stuttgart. Co-authors on the papers here include Florian Laws.
Helmut Schmid has 3 papers in our library, in 2004–2008, most of them on Part-of-speech tagging, Morphology, Syntax & grammar formalisms; often with Florian Laws.
current affiliationTechnische Universität Darmstadt, Darmstadt, Germany; Munich Center for Machine Learning, Munich; Ludwig-Maximilians-Universität München, Munich, Germany
OpenAlex · ORCID · h-index 24 · 93 works · 2 962 citations OpenAlex, 2026-10-14
3 works in our library · 409 citations in our library · 6 more works in our library · ⭐ Paper Star rank #2462
Affiliations
- Ludwig-Maximilians-Universität München · Munich, Germany — current · 2013–2026 on 54 papers
- Munich Center for Machine Learning · Munich — current · 2026 on 1 paper
- Technische Universität Darmstadt · Darmstadt, Germany — current · 2026 on 1 paper
- University of Maryland, College Park · College Park, United States — 2024 on 2 papers
- University of Stuttgart · Stuttgart, Germany — 2000–2013 on 32 papers
Topics
Works by year
2000s
Papers
- Estimation of Conditional Probabilities With Decision Trees and an Application to Fine-Grained POS Tagging (2008 · 254 citations)
The paper tackles HMM part-of-speech tagging with very large, morphologically detailed tagsets, such as the Tiger treebank tagset for German (over 700 tags) and the Czech Academic Corpus tagset (about 1200 tags). - SMOR: A German Computational Morphology Covering Derivation, Composition and Inflection (2004 · 244 citations)
SMOR addresses a gap in German computational morphology. Earlier finite-state systems either depended mainly on large word lists (WordManager, GerTWOL) or handled only part of the problem: DMOR has no derivation component, and DeKo has no inflection. SMOR covers productive derivation, composition and inflection in a… - Efficient Parsing of Highly Ambiguous Context-Free Grammars with Bit Vectors (2004 · 209 citations)
Treebank-derived context-free grammars give good coverage but are massively ambiguous. Ordinary chart parsers often exhaust memory or time on them, especially when every analysis is needed and not only the single best one. Schmid presents BitPar, a CKY-style parser that keeps the number of edges and instead makes…
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