The groundbreaking innovations of Hermann Ney have led to major advances in speech and language processing and sparked a new era of research in automatic recognition and translation of spoken language. His dynamic programming-based techniques made search/decoding processes computationally feasible for large-vocabulary continuous speech recognition. He developed a statistical smoothing technique, now known as the Kneser-Ney smoothing process, which is one of the most efficient and widely used methods for language model smoothing. Ney also created phrase-based machine translation, which outperformed conventional linguistic systems in translating spoken language. His publicly available GIZA++ toolkit for statistical word alignment has become the standard for building state-of-the-art machine translation systems. Ney’s contributions have greatly impacted today’s speech interfaces for mobile devices, among other applications.
An IEEE Fellow, Ney is a professor with the RWTH Aachen University of Technology, Aachen, Germany.