What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Natural language processing
Franz Josef Och mainly focuses on Artificial intelligence, Machine translation, Natural language processing, Interactive machine translation and Translation.
His is doing research in BLEU, Evaluation of machine translation, Transfer-based machine translation, Example-based machine translation and Phrase, both of which are found in Artificial intelligence.
In Evaluation of machine translation, Franz Josef Och works on issues like Synchronous context-free grammar, which are connected to Hybrid machine translation.
Franz Josef Och interconnects Machine learning, Speech recognition, Word error rate and Pattern recognition in the investigation of issues within Machine translation.
His Natural language processing study focuses on Computer-assisted translation in particular.
In his work, Multilingualism, Speech translation and Context is strongly intertwined with Natural language, which is a subfield of Interactive machine translation.
His most cited work include:
- A systematic comparison of various statistical alignment models (3602 citations)
- Statistical phrase-based translation (3115 citations)
- Minimum Error Rate Training in Statistical Machine Translation (2584 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Machine translation, Natural language processing, Translation and Speech recognition.
His Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Transfer-based machine translation and BLEU study in the realm of Machine translation connects with subjects such as Quality.
His work on Rule-based machine translation, Phrase and Interactive machine translation is typically connected to Cache language model as part of general Natural language processing study, connecting several disciplines of science.
His work carried out in the field of Interactive machine translation brings together such families of science as Hybrid machine translation and Word error rate.
Franz Josef Och is studying Machine translation software usability, which is a component of Example-based machine translation.
He most often published in these fields:
- Artificial intelligence (73.86%)
- Machine translation (65.91%)
- Natural language processing (56.82%)
What were the highlights of his more recent work (between 2010-2018)?
- Artificial intelligence (73.86%)
- Machine translation (65.91%)
- Natural language processing (56.82%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Machine translation, Natural language processing, Speech recognition and Computational biology.
His Artificial intelligence study typically links adjacent topics like Machine learning.
His Machine translation research includes themes of Domain, Algorithm and Translation.
His Algorithm research is multidisciplinary, relying on both Domain adaptation, Translation system, Domain model and Transfer-based machine translation.
His Sentence study, which is part of a larger body of work in Natural language processing, is frequently linked to Lexical choice and Novelty, bridging the gap between disciplines.
His studies deal with areas such as Simple LR parser, LR parser, Parsing and Component as well as Speech recognition.
Between 2010 and 2018, his most popular works were:
- Deep sequencing of 10,000 human genomes. (218 citations)
- Unsupervised Morphology Induction Using Word Embeddings (99 citations)
- Identification of individuals by trait prediction using whole-genome sequencing data (77 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
Franz Josef Och mostly deals with Computational biology, Genetics, Natural language processing, Artificial intelligence and Pattern recognition.
Computational biology and Personalized medicine are frequently intertwined in his study.
His Genetics study spans across into areas like Genotyping, Nanopore sequencing, STR multiplex system, STR analysis and Human genome.
His Natural language processing research integrates issues from Speech recognition and Translation.
His Component research extends to Artificial intelligence, which is thematically connected.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Range, Word and Morphology.
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