World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
26337
World Ranking
4945
National Ranking
2298

Overview

Franz Josef Och is affiliated with Google in the United States. Their professional focus and research contributions are primarily linked to this organization.

There are no specific recent papers, co-authors, or publication venues recorded for Franz Josef Och in the provided data. Similarly, no detailed information is available about books they have published or the main and subfields of study.

The profile does not include main topics of work or awards received by this scientist. There is no indication that they are deceased.

Given the limited data available, the professional overview of Franz Josef Och emphasizes affiliation without further details on research output or subject matter specialization.

Best Publications

  • A systematic comparison of various statistical alignment models

    Franz Josef Och;Hermann Ney

  • Minimum Error Rate Training in Statistical Machine Translation

    Franz Josef Och

  • Statistical phrase-based translation

    Philipp Koehn;Franz Josef Och;Daniel Marcu

  • Discriminative Training and Maximum Entropy Models for Statistical Machine Translation

    Franz Josef Och;Hermann Ney

  • Improved statistical alignment models

    Franz Josef Och;Hermann Ney

  • The Alignment Template Approach to Statistical Machine Translation

    Franz Josef Och;Hermann Ney

  • Improved Alignment Models for Statistical Machine Translation

    Franz Josef Och;Christoph Tillmann;Hermann Ney

  • Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics

    Chin-Yew Lin;Franz Josef Och

  • Large Language Models in Machine Translation

    Thorsten Brants;Ashok C. Popat;Peng Xu;Franz J. Och

  • Phrase-Based Statistical Machine Translation

    Richard Zens;Franz Josef Och;Hermann Ney

  • Deep sequencing of 10,000 human genomes.

    Amalio Telenti;Levi C. T. Pierce;William H. Biggs;Julia di Iulio

  • An Evaluation Tool for Machine Translation: Fast Evaluation for MT Research

    Sonja Nießen;Franz Josef Och;Gregor Leusch;Hermann Ney

  • Lattice-based Minimum Error Rate Training for Statistical Machine Translation

    Wolfgang Macherey;Franz Och;Ignacio Thayer;Jakob Uszkoreit

  • ORANGE: a method for evaluating automatic evaluation metrics for machine translation

    Chin-Yew Lin;Franz Josef Och

  • A Smorgasbord of Features for Statistical Machine Translation

    Franz Josef Och;Daniel Gildea;Sanjeev Khudanpur;Anoop Sarkar

  • An efficient method for determining bilingual word classes

    Franz Josef Och

  • Maximum entropy models for named entity recognition

    Oliver Bender;Franz Josef Och;Hermann Ney

  • A comparison of alignment models for statistical machine translation

    Franz Josef Och;Hermann Ney

  • Discriminative Reranking for Machine Translation

    Libin Shen;Anoop Sarkar;Franz Josef Och

  • Statistical machine translation : from single word models to alignment templates

    Franz Josef Och;Hermann Ney

Frequent Co-Authors

Hermann Ney
Hermann Ney RWTH Aachen University
Jeffrey Dean
Jeffrey Dean Google (United States)
J. Craig Venter
J. Craig Venter J. Craig Venter Institute
Amalio Telenti
Amalio Telenti VIR Biotechnology (United States)
Daniel Keysers
Daniel Keysers Google (United States)
Stephan Vogel
Stephan Vogel University of Graz
Francisco Casacuberta
Francisco Casacuberta Universitat Politècnica de València
Victor Lavrenko
Victor Lavrenko University of Edinburgh
Haibao Tang
Haibao Tang Fujian Agriculture and Forestry University

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