World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
8515
World Ranking
11030
National Ranking
3

Overview

Luciana Ferrer is affiliated with the University of Buenos Aires in Argentina. Their research primarily lies in the field of Computer Science, with a focus on subfields such as Artificial Intelligence, Signal Processing, Health Informatics, Radiology, Nuclear Medicine and Imaging, and Social Psychology.

The scientist's main topics of work include:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Artificial Intelligence in Healthcare and Education
  • Speech and Audio Processing
  • COVID-19 diagnosis using AI
  • Speech and dialogue systems
  • Explainable Artificial Intelligence (XAI)

Luciana Ferrer has contributed to various academic venues, with frequent publications in:

  • arXiv (Cornell University)
  • Nature Methods
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • European Radiology
  • Computer Speech & Language

Some recent papers by the scientist include:

  • Metrics reloaded: recommendations for image analysis validation, 2024, Nature Methods
  • Understanding metric-related pitfalls in image analysis validation, 2024, Nature Methods
  • Metrics reloaded: Recommendations for image analysis validation, 2022, arXiv (Cornell University)
  • Class imbalance on medical image classification: towards better evaluation practices for discrimination and calibration performance, 2024, European Radiology
  • Understanding metric-related pitfalls in image analysis validation, 2023, arXiv (Cornell University)

Frequent co-authors working alongside Luciana Ferrer include:

  • Pablo Riera
  • Leonardo Pepino
  • Annika Reinke
  • Patrick Godau
  • Minu D. Tizabi

Best Publications

  • The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

    Ron Caspi;Richard Billington;Luciana Ferrer;Hartmut Foerster

  • A novel scheme for speaker recognition using a phonetically-aware deep neural network

    Yun Lei;Nicolas Scheffer;Luciana Ferrer;Mitchell McLaren

  • Method and apparatus for tailoring the output of an intelligent automated assistant to a user

    Gokhan Tur;Horacio E. Franco;Elizabeth Shriberg;Gregory K. Myers

  • Modeling prosodic feature sequences for speaker recognition

    Elizabeth Shriberg;Elizabeth Shriberg;Luciana Ferrer;Luciana Ferrer;Sachin S. Kajarekar;Anand Venkataraman

  • The Speakers in the Wild (SITW) Speaker Recognition Database.

    Mitchell McLaren;Luciana Ferrer;Diego Castan;Aaron Lawson

  • Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings

    Leonardo Pepino;Pablo Riera;Luciana Ferrer

  • MLLR transforms as features in speaker recognition.

    Andreas Stolcke;Luciana Ferrer;Sachin S. Kajarekar;Elizabeth Shriberg

  • Advances in deep neural network approaches to speaker recognition

    Mitchell McLaren;Yun Lei;Luciana Ferrer

  • Is the speaker done yet? faster and more accurate end-of-utterance detection using prosody.

    Luciana Ferrer;Elizabeth Shriberg;Andreas Stolcke

  • Towards noise-robust speaker recognition using probabilistic linear discriminant analysis

    Yun Lei;Lukas Burget;Luciana Ferrer;Martin Graciarena

  • Speaker Recognition With Session Variability Normalization Based on MLLR Adaptation Transforms

    A. Stolcke;S.S. Kajarekar;L. Ferrer;E. Shrinberg

  • Nonparametric feature normalization for SVM-based speaker verification

    A. Stolcke;S. Kajarekar;L. Ferrer

  • Study of senone-based deep neural network approaches for spoken language recognition

    Luciana Ferrer;Yun Lei;Mitchell McLaren;Nicolas Scheffer

  • Application of Convolutional Neural Networks to Language Identification in Noisy Conditions

    Yun Lei;Luciana Ferrer;Aaron Lawson;Mitchell McLaren

  • A prosody-based approach to end-of-utterance detection that does not require speech recognition

    L. Ferrer;E. Shriberg;A. Stolcke

  • Application of convolutional neural networks to speaker recognition in noisy conditions.

    Mitchell McLaren;Yun Lei;Nicolas Scheffer;Luciana Ferrer

  • Modeling duration patterns for speaker recognition

    Luciana Ferrer;Harry Bratt;Venkata Ramana Rao Gadde;Sachin S. Kajarekar

  • THE SRI NIST 2008 speaker recognition evaluation system

    Sachin S. Kajarekar;Nicolas Scheffer;Martin Graciarena;Elizabeth Shriberg

  • Prosodic knowledge sources for automatic speech recognition

    D. Vergyri;A. Stolcke;V.R.R. Gadde;L. Ferrer

  • SRI's 2004 NIST speaker recognition evaluation system

    S.S. Kajarekar;L. Ferrer;E. Shriberg;K. Sonmez

Frequent Co-Authors

Elizabeth Shriberg
Elizabeth Shriberg International Computer Science Institute
Horacio Franco
Horacio Franco SRI International
Lukas Burget
Lukas Burget Brno University of Technology
Gokhan Tur
Gokhan Tur Amazon (United States)
Abeer Alwan
Abeer Alwan University of California, Los Angeles
Dilek Hakkani-Tur
Dilek Hakkani-Tur University of Illinois at Urbana-Champaign
Charles R. Marmar
Charles R. Marmar New York University
Peter D. Karp
Peter D. Karp SRI International
Lukas A. Mueller
Lukas A. Mueller Boyce Thompson 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

Expanding your education with online degrees in technical fields opens doors to a variety of career paths in the USA and beyond. Besides Computer Science, many students are considering online alternatives in adjacent disciplines such as engineering, data science, and physics.

For a hands-on approach to design and innovation, check out the cheapest mechanical engineering degree online to gain practical skills for in-demand engineering positions. If you’re drawn to cutting-edge technology, numerous accredited online electrical engineering programs can provide rigorous training from a distance.

Those interested in analytics and data-driven careers might ask, what is the cheapest data science course in the us? There are options designed to be both affordable and highly respected. Similarly, if your interests are rooted in foundational sciences, pursuing a physics degree online can equip you for research, education, and high-tech industries.

Exploring these related fields can complement your computer science studies and broaden your professional opportunities in today’s competitive job market.

Best Scientists Citing Luciana Ferrer

Trending Scientists