2014 - IEEE Fellow For contributions to spoken language processing
Dilek Hakkani-Tur mainly focuses on Artificial intelligence, Natural language processing, Speech recognition, Spoken language and Natural language. Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Set. Her Natural language processing research includes elements of Context, Spoken dialog systems, Dialog system and Utterance.
Dilek Hakkani-Tur has researched Speech recognition in several fields, including Sentence, Segmentation, Unsupervised learning and Feature extraction. Her biological study spans a wide range of topics, including Recurrent neural network, Computational linguistics, Semantics, Discriminative model and Robustness. Her Natural language study combines topics in areas such as Classifier and Transcription.
Her main research concerns Artificial intelligence, Natural language processing, Speech recognition, Spoken language and Natural language. Her Artificial intelligence research incorporates themes from Context and Dialog box. She interconnects Conversation and Human–computer interaction in the investigation of issues within Dialog box.
Her Natural language processing study combines topics from a wide range of disciplines, such as Domain, Dialog system, Set and Information retrieval. Her studies deal with areas such as Boosting and Segmentation as well as Speech recognition. Her studies in Spoken language integrate themes in fields like Conditional random field, Classifier, Word, Deep learning and Discriminative model.
Her primary scientific interests are in Artificial intelligence, Natural language processing, Dialog box, Human–computer interaction and Domain. Her Artificial intelligence study incorporates themes from Machine learning, State and Reading comprehension. Her Natural language processing research integrates issues from Ontology and Context.
Dilek Hakkani-Tur has included themes like Natural language generation, Conversation and Open domain in her Dialog box study. Her Human–computer interaction research incorporates elements of Task oriented, Natural language and Selection. Her work deals with themes such as Recurrent neural network, Speech recognition, Encoding and Spoken language, which intersect with Word.
Her scientific interests lie mostly in Artificial intelligence, Natural language processing, State, Human–computer interaction and Dialog box. Specifically, her work in Artificial intelligence is concerned with the study of Training set. Dilek Hakkani-Tur mostly deals with Automatic summarization in her studies of Natural language processing.
Her Human–computer interaction research is multidisciplinary, incorporating elements of Domain, Task oriented, Dialog system and Reinforcement learning. Her Dialog box study which covers Conversation that intersects with SIGNAL, Relevance and Chatbot. Her study in Machine learning is interdisciplinary in nature, drawing from both Tracking and Set.
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Prosody-based automatic segmentation of speech into sentences and topics
Elizabeth Shriberg;Andreas Stolcke;Dilek Hakkani-Tür;Gükhan Tür.
Speech Communication (2000)
Using recurrent neural networks for slot filling in spoken language understanding
Grégoire Mesnil;Yann Dauphin;Kaisheng Yao;Yoshua Bengio.
IEEE Transactions on Audio, Speech, and Language Processing (2015)
Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM.
Dilek Hakkani-Tür;Gokhan Tur;Asli Celikyilmaz;Yun-Nung Chen.
conference of the international speech communication association (2016)
Combining active and semi-supervised learning for spoken language understanding
Dilek Z. Hakkani-Tur;Robert Elias Schapire;Gokhan Tur.
Speech Communication (2005)
Building a Turkish Treebank
Kemal Oflazer;Bilge Say;Dilek Zeynep Hakkani-Tür;Gökhan Tür.
The CALO Meeting Assistant System
G Tur;A Stolcke;L Voss;S Peters.
IEEE Transactions on Audio, Speech, and Language Processing (2010)
What is left to be understood in ATIS
Gokhan Tur;Dilek Hakkani-Tur;Larry Heck.
spoken language technology workshop (2010)
Library of existing spoken dialog data for use in generating new natural language spoken dialog systems
Lee Begeja;Giuseppe Di Fabbrizio;David Crawford Gibbon;Dilek Z. Hakkani-Tur.
Statistical Morphological Disambiguation for Agglutinative Languages
Dilek Z. Hakkani-Tür;Kemal Oflazer;Gökhan Tür.
Computers and The Humanities (2002)
The CALO meeting speech recognition and understanding system
G. Tur;A. Stolcke;L. Voss;J. Dowding.
spoken language technology workshop (2008)
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