2017 - IEEE Fellow For contributions to text-to-speech synthesis and spoken language understanding
2017 - Member of the National Academy of Engineering For contributions to the use of prosody in text-to-speech and spoken dialogue systems, and to audio browsing and retrieval.
2015 - ACM Fellow For contributions to spoken language processing.
Her scientific interests lie mostly in Natural language processing, Artificial intelligence, Speech recognition, Structure and Intonation. Her Natural language processing study integrates concerns from other disciplines, such as Variation, Utterance, Speech synthesis and Set. As part of her studies on Artificial intelligence, she often connects relevant areas like Reliability.
The study incorporates disciplines such as Recall, Mexican Spanish, Phrase and Statistical model in addition to Speech recognition. The Intonation study which covers Pitch accent that intersects with Interpretation, Meaning, Orthography, Part of speech and Adverbial. Her Speech corpus research is multidisciplinary, relying on both Prosody and Subject.
Julia Hirschberg focuses on Artificial intelligence, Natural language processing, Speech recognition, Prosody and Information technology. Her work carried out in the field of Artificial intelligence brings together such families of science as Variation, Context and Set. Her Natural language processing research incorporates elements of Speech corpus and Speech synthesis.
Her Speech recognition research is multidisciplinary, incorporating perspectives in Segmentation, American English and Word. Julia Hirschberg performs integrative Information technology and Presentation research in her work.
Her primary scientific interests are in Artificial intelligence, Natural language processing, Speech recognition, Deception and Entrainment. She interconnects Prosody and Set in the investigation of issues within Artificial intelligence. Her biological study deals with issues like Code, which deal with fields such as Focus and Named-entity recognition.
Her work in the fields of Speech recognition, such as Speech synthesis, Utterance and Word error rate, overlaps with other areas such as Data selection and Naturalness. Her research in Speech synthesis intersects with topics in Hidden Markov model and Machine translation. As part of one scientific family, she deals mainly with the area of Deception, narrowing it down to issues related to the Cognitive psychology, and often Perception.
Her main research concerns Artificial intelligence, Natural language processing, Deception, Speech recognition and Entrainment. Her study brings together the fields of Chemistry and Artificial intelligence. She incorporates Natural language processing and Code in her studies.
Her studies in Deception integrate themes in fields like Cognitive psychology, Set, Phonotactics, Applied psychology and Personality. Julia Hirschberg studies Word error rate which is a part of Speech recognition. The concepts of her Utterance study are interwoven with issues in Annotation and Intelligibility.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The meaning of intonational contours in the interpretation of discourse
Janet Pierrehumbert;Julia Bell Hirschberg.
Intentions in Communication (1990)
TOBI: a standard for labeling English prosody.
Kim E. A. Silverman;Mary E. Beckman;John F. Pitrelli;Mari Ostendorf.
conference of the international speech communication association (1992)
V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure
Andrew Rosenberg;Julia Hirschberg.
empirical methods in natural language processing (2007)
A theory of scalar implicature
Julia Linn Bell Hirschberg.
Advances in natural language processing.
Julia Hirschberg;Christopher D. Manning.
The original ToBI system and the evolution of the ToBI framework
Mary E. Beckman;Julia Hirschberg;Stefanie Shattuck-Hufnagel.
Tonal alignment patterns in Spanish
Pilar Prieto;Jan van Santen;Julia Hirschberg.
Journal of Phonetics (1995)
Implicating Uncertainty: The Pragmatics of Fall-Rise Intonation
Gregory Ward;Julia Hirschberg.
Evaluation of prosodic transcription labeling reliability in the tobi framework.
John F. Pitrelli;Mary E. Beckman;Julia Hirschberg.
conference of the international speech communication association (1994)
Detecting Hate Speech on the World Wide Web
William Warner;Julia Hirschberg.
Proceedings of the Second Workshop on Language in Social Media (2012)
Profile was last updated on December 6th, 2021.
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