What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Machine learning
- Speech recognition
Katrin Kirchhoff mostly deals with Speech recognition, Artificial intelligence, Natural language processing, Language model and Speech processing. Her research in the fields of Acoustic model overlaps with other disciplines such as VOCAL PARAMETERS. The various areas that Katrin Kirchhoff examines in her Artificial intelligence study include Pronunciation and Ranking, Machine learning.
Her research in Natural language processing focuses on subjects like Arabic, which are connected to Trigram, Treebank, Context and Bigram. Her biological study spans a wide range of topics, including Natural language and Speech synthesis. Her research in Pattern recognition intersects with topics in Artificial neural network, Feature and Conversational speech.
Her most cited work include:
- Factored language models and generalized parallel backoff (268 citations)
- Error-correction detection and response generation in a spoken dialogue system (185 citations)
- Robust speech recognition using articulatory information (183 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Artificial intelligence, Speech recognition, Natural language processing, Machine translation and Machine learning. As part of her studies on Artificial intelligence, she frequently links adjacent subjects like Pattern recognition. Katrin Kirchhoff interconnects Vocabulary and Robustness in the investigation of issues within Speech recognition.
Her research investigates the connection with Natural language processing and areas like Arabic which intersect with concerns in Transcription. The concepts of her Machine translation study are interwoven with issues in Translation and Phrase. Her study in the field of Semi-supervised learning and Selection is also linked to topics like Submodular set function.
She most often published in these fields:
- Artificial intelligence (66.67%)
- Speech recognition (51.16%)
- Natural language processing (37.98%)
What were the highlights of her more recent work (between 2018-2021)?
- Speech recognition (51.16%)
- Artificial intelligence (66.67%)
- Language model (18.60%)
In recent papers she was focusing on the following fields of study:
Katrin Kirchhoff mainly investigates Speech recognition, Artificial intelligence, Language model, Encoder and Machine learning. Her study on Speech recognition is mostly dedicated to connecting different topics, such as Punctuation. Her research in Artificial intelligence is mostly focused on Preprocessor.
Much of her study explores Language model relationship to Fluency. Her Machine learning research is multidisciplinary, incorporating perspectives in Inverse, Representation and Inference. Her Utterance research includes elements of Conversation, Language recognition and Word error rate.
Between 2018 and 2021, her most popular works were:
- Masked Language Model Scoring (31 citations)
- Simple, Fast, Accurate Intent Classification and Slot Labeling for Goal-Oriented Dialogue Systems. (15 citations)
- Multi-stream Network With Temporal Attention For Environmental Sound Classification (11 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Natural language processing
Katrin Kirchhoff focuses on Artificial intelligence, Speech recognition, Machine learning, Representation and Inference. Her Artificial intelligence study frequently intersects with other fields, such as Pattern recognition. Her study in Speech recognition is interdisciplinary in nature, drawing from both Variety and BLEU.
Her Machine learning research integrates issues from Class and Joint. Her Representation research is multidisciplinary, relying on both Task and Spoken language.
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