37.2656, Support: Upper German; German, Swabian; Computational Linguistics, Phonetics: PhD, University of Tübingen, Department of Linguistics

[The LINGUIST List]

LINGUIST List: Vol-37-2656. Thu Aug 13 2026. ISSN: 1069 - 4875.

Subject: 37.2656, Support: Upper German; German, Swabian; Computational Linguistics, Phonetics: PhD, University of Tübingen, Department of Linguistics

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Date: 12-Aug-2026
From: Gerhard Jäger [gerhard.jaeger at uni-tuebingen.de]
Subject: Upper German; German, Swabian; Computational Linguistics, Phonetics: PhD, University of Tübingen, Department of Linguistics


Institution/Organization: University of Tübingen, Department of
Linguistics
Web Address: https://uni-tuebingen.de/en/26

Level: PhD

Duties: Research

Specialty Areas: Computational Linguistics; Phonetics
Required Language(s): German (deu)
                      Swabian (swg, swab1242)
                      Upper German (high1286)

Description:

Doctoral Researcher (m/f/d) in Dialect-Aware Automatic Speech
Recognition
University of Tübingen (TV-L E13, 75%, 3+1 years)
The project "Automatic Swabian Recognition (ASR): Processing and
Evaluating Dialect Speech" is a network project funded by the
Innovation Fund of the Cluster of Excellence "Machine Learning: New
Perspectives for Science" at the University of Tübingen. Its core
resource is the Arno Ruoff Archive, around 1,600 interviews with
speakers of Upper German dialects recorded between 1950 and 1975. The
project makes this material accessible through a dialect-adapted
speech-recognition and IPA-transcription pipeline and releases it as
an open benchmark dataset. It unites computational linguistics,
machine learning, and cultural anthropology.
For the ASR project, the Department of Linguistics at the University
of Tübingen, in cooperation with the Hertie Institute for AI in Brain
Health, is seeking to fill the position of a Doctoral Researcher
(m/f/d) in dialect-aware automatic speech recognition (TV-L E13, 75%,
for 3+1 years), starting at the earliest possible date. The position
is jointly supervised by Prof. Dr. Kerstin Ritter (Hertie Institute
for AI in Brain Health) and Prof. Dr. Gerhard Jäger (Department of
Linguistics); the doctoral researcher will pursue a dissertation
within the project's framework.
State-of-the-art speech recognition reaches near-human accuracy on
standard languages but degrades sharply on regional dialects,
historical recordings, and spontaneous speech, precisely the
conditions of the Arno Ruoff Archive. Building on self-supervised
speech representations, the dissertation develops dialect-aware ASR
and IPA transcription that models pronunciation variability,
code-switching, and recognition uncertainty. Its central deliverable
is an open benchmark dataset of audio, orthographic, and IPA tiers,
together with the models that produce it. The methodological core is
uncertainty-aware, low-resource ASR whose adaptation strategies
transfer to other under-resourced varieties. A second strand extends
the models to longitudinal clinical recordings from the Tübingen TREND
cohort, where speech serves as a non-invasive marker of cognitive
change and neurodegeneration; bridging these archival and clinical
domains is itself a central methodological challenge.
Candidates with a background in machine learning, computer science,
computational linguistics, data science, or a related field, and an
interest in speech technology and low-resource machine learning, are
particularly encouraged to apply. The position requires strong
programming skills (Python and a deep-learning framework such as
PyTorch). Experience with speech or audio processing, self-supervised
learning, or sequence models is a plus. Knowledge of German helps with
the dialect material; familiarity with a southern German dialect
(Swabian or Alemannic) is welcome but not required.
The salary follows the union contract TV-L, E13 (75%). The position is
funded for three years, with the possibility of a one-year extension
(3+1).
Applications should include a CV, a statement of research interests
and relevant experience, and the names of up to two references. The
position will be filled as soon as possible; the deadline for
applications is September 30, 2026.
Disabled applicants will be preferred if they have the same
qualifications as non-disabled applicants. The University of Tübingen
strives to increase the proportion of women in research, and therefore
encourages qualified female scientists to apply.
Please send your application electronically as a single pdf file to
as at semsprach.uni-tuebingen.de.
The project also funds a second doctoral position, on modeling
narrative knowledge in cultural context, supervised by Prof. Dr. Lea
Frermann, Dr. Valeska Flor, and Prof. Dr. Thomas Thiemeyer. Details on
both positions are available at https://uni-tuebingen.de/en/299892.

Application Deadline: 30-Sep-2026
Application Instructions:
Please send your application as a single PDF file, including a CV, a
statement of research interests and relevant experience, and the names
of up to two references.

Web Address for Applications: https://uni-tuebingen.de/en/299892
Email Address for Applications: as at semsprach.uni-tuebingen.de

Contact Information:
Gerhard Jäger
Contact Email: gerhard.jaeger at uni-tuebingen.de



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