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Dialect-Aware Natural Language Processing for Low-Resource Languages

I am Christian Schuler, a PhD candidate in Computational Linguistics at Saarland University (UdS) affiliated with the German Research Center for Artificial Intelligence (DFKI), specifically the Department of Multilinguality and Language Technology (MLT). Under the supervision of Prof. Dr. Josef van Genabith and Prof. Dr. Timo Baumann, and in close-collaboration with Dr. Simon Ostermann's E&E research group, I work on Dialect-Aware Natural Language Processing for Low-Resource Languages.

My current research focuses on developing robust techniques for language identification (LID) and automatic speech recognition (ASR), with an initial emphasis on Kurdish varieties. More broadly, I am interested in how dialect-aware and multilingual NLP can support linguistic diversity, improve the accessibility of language technologies, and strengthen cross-cultural communication, for which I also tackle machine translation (MT). Guided by the motto 生于忧患，死于安乐, I believe that focusing primarily on high-resource languages like English risks leaving our field fragile and incomplete.

My work therefore seeks to build more resilient and inclusive language technologies by tackling the challenges of low-resource and dialectal settings. This motivation builds upon my previous research done at University of Hamburg: my Master’s thesis, “Leveraging Morphological and Lexical Features in Synthetic Data Generation for Dialect-Specific Machine Translation” (supervised by Dr. Sina Ahmadi, Dr. Seid Muhie Yimam, and Prof. Dr. Chris Biemann), and my Bachelor’s thesis, “Perceptual Quality Assessment of Lip-Synchrony in Dubbing” (supervised by Prof. Dr. Timo Baumann and Prof. Dr. Timo Gerkmann), which first sparked my interest in the interplay between language and technology.

I believe that true progress requires a joint effort by NLP-practitioners, linguists, and language communities! Working together is the only way forward, so if any of this sounds interesting to you, don't hesitate to contact me directly to discuss a possible collaboration! I also very much enjoy teaching and supervising students and if you happen to be interested in exploring similar ideas or even already consider doing your thesis on a related topic, feel free to send me a short introduction of who you are and what you would like to do.