Hermann Ney

Hermann Ney

Awards

IEEE James L. Flanagan Speech and Audio Processing Award

Biography

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.