World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
7692
World Ranking
7251
National Ranking
3163

Overview

Katrin Kirchhoff is a researcher affiliated with Amazon in the United States, with a primary focus on computer science through various subfields including artificial intelligence and signal processing. Their scholarly work predominantly explores topics such as speech recognition and synthesis, natural language processing techniques, and topic modeling, contributing to advances in audio and dialogue systems and emotion recognition.

The main topics addressed in their research are:

  • Speech Recognition and Synthesis
  • Natural Language Processing Techniques
  • Topic Modeling
  • Music and Audio Processing
  • Speech and Audio Processing
  • Speech and dialogue systems
  • Emotion and Mood Recognition

Their publication record spans several notable venues, reflecting an active engagement with established conferences and journals in their field. Frequent publication venues include:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • 2022 IEEE Spoken Language Technology Workshop (SLT)
  • IEEE Journal of Selected Topics in Signal Processing

Katrin Kirchhoff has coauthored many works alongside several prominent collaborators, highlighting a collaborative research approach. Frequent co-authors are:

  • Sravan Bodapati
  • Sundararajan Srinivasan
  • Saket Dingliwal
  • Srikanth Ronanki
  • Monica Sunkara

Recent papers by Katrin Kirchhoff include:

  • Self-Supervised Speech Representation Learning: A Review, 2022, IEEE Journal of Selected Topics in Signal Processing
  • Representation Learning Through Cross-Modal Conditional Teacher-Student Training For Speech Emotion Recognition, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Personalization of CTC Speech Recognition Models, 2023, 2022 IEEE Spoken Language Technology Workshop (SLT)
  • Listen, Know and Spell: Knowledge-Infused Subword Modeling for Improving ASR Performance of OOV Named Entities, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models, 2024, arXiv (Cornell University)

The research contributions by Kirchhoff cover a wide range of topics within computer science, emphasizing speech and audio processing techniques and multimodal machine learning applications.

Best Publications

  • Masked Language Model Scoring

    Julian Salazar;Davis Liang;Toan Q. Nguyen;Katrin Kirchhoff

  • Self-Supervised Speech Representation Learning: A Review

    Unknown

  • Factored language models and generalized parallel backoff

    Jeff A. Bilmes;Katrin Kirchhoff

  • Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

    Lucy Vanderwende;Hal Daumé;Katrin Kirchhoff

  • Robust speech recognition using articulatory information

    Katrin Kirchhoff

  • Combining acoustic and articulatory feature information for robust speech recognition

    Katrin Kirchhoff;Gernot A Fink;Gerhard Sagerer

  • Multilingual Speech Processing

    Tanja Schultz;Katrin Kirchhoff

  • Error-correction detection and response generation in a spoken dialogue system

    Ivan Bulyko;Katrin Kirchhoff;Mari Ostendorf;J. Goldberg

  • Novel approaches to Arabic speech recognition: report from the 2002 Johns-Hopkins Summer Workshop

    K. Kirchhoff;J. Bilmes;S. Das;N. Duta

  • Deep Contextualized Acoustic Representations for Semi-Supervised Speech Recognition

    Shaoshi Ling;Yuzong Liu;Julian Salazar;Katrin Kirchhoff

  • Morphology-Based Language Modeling for Arabic Speech Recognition

    Dimitra Vergyri;Katrin Kirchhoff;Kevin Duh;Andreas Stolcke

  • Automatic diacritization of Arabic for acoustic modeling in speech recognition

    Dimitra Vergyri;Katrin Kirchhoff

  • Morphology-based language modeling for conversational Arabic speech recognition

    Katrin Kirchhoff;Dimitra Vergyri;Jeff A. Bilmes;Kevin Duh

  • Landmark-based speech recognition: report of the 2004 Johns Hopkins summer workshop

    M. Hasegawa-Johnson;J. Baker;S. Borys;K. Chen

  • Combining articulatory and acoustic information for speech recognition in noisy and reverberant environments

    Katrin Kirchhoff

  • Self-attention Networks for Connectionist Temporal Classification in Speech Recognition

    Julian Salazar;Katrin Kirchhoff;Zhiheng Huang

  • Learning to rank with partially-labeled data

    Kevin Duh;Katrin Kirchhoff

  • Factored Neural Language Models

    Andrei Alexandrescu;Katrin Kirchhoff

  • The Vocal Joystick: A Voice-Based Human-Computer Interface for Individuals with Motor Impairments

    Jeff A. Bilmes;Xiao Li;Jonathan Malkin;Kelley Kilanski

  • Recent innovations in speech-to-text transcription at SRI-ICSI-UW

    A. Stolcke;Barry Chen;H. Franco;Venkata Ramana Rao Gadde

  • SUBMODULAR SUBSET SELECTION FOR LARGE-SCALE SPEECH TRAINING DATA

    Kai Wei;Yuzong Liu;Katrin Kirchhoff;Chris D. Bartels

Frequent Co-Authors

Jeff A. Bilmes
Jeff A. Bilmes University of Washington
Kevin Duh
Kevin Duh Johns Hopkins University
Tanja Schultz
Tanja Schultz University of Bremen
Mari Ostendorf
Mari Ostendorf University of Washington
Gernot A. Fink
Gernot A. Fink TU Dortmund University
Howard Jay Chizeck
Howard Jay Chizeck University of Washington
James A. Landay
James A. Landay Stanford University
Richard Wright
Richard Wright Georgia State University
Nelson Morgan
Nelson Morgan International Computer Science Institute

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens the door to a diverse range of online degree options and career paths. Many students choose programs from nationally accredited online colleges to ensure flexibility and recognized credentials while balancing work, family, and studies.

Specialized online programs, such as those offered by online school for game design, can lead to creative and technical roles in the growing gaming industry. If you’re passionate about network security or cyber defense, earning an online cybersecurity degree can jumpstart a career protecting organizations from digital threats.

For those interested in applying computing to real-world projects, a master of construction management may combine technology and leadership to prepare graduates for management roles in the construction field.

These online learning pathways provide flexibility, affordability, and targeted skill development, empowering students to shape their future careers in technology-driven fields.

Best Scientists Citing Katrin Kirchhoff

Trending Scientists