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D-Index & Metrics

Computer Science

D-Index
54
Citations
10261
World Ranking
4622
National Ranking
2148

Overview

Florian Metze is affiliated with Carnegie Mellon University in the United States and specializes in computer science with a focus on artificial intelligence, computer vision and pattern recognition, and signal processing. Their publication record includes 125 works predominantly in these fields, reflecting a comprehensive engagement with areas such as speech recognition and synthesis, music and audio processing, and natural language processing techniques.

Their research covers multiple main topics including:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and Audio Processing
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning

Florian Metze has contributed to various frequent publication venues, showcasing a range of interdisciplinary approaches. These venues include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Recent notable papers include:

  • "VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding," 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • "How2Sign: A large-scale multimodal dataset for continuous American sign language," 2021, UPCommons (Polytechnic University of Catalonia)
  • "Masked Autoencoders that Listen," 2022, arXiv (Cornell University)
  • "Self-supervised object detection from audio-visual correspondence," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Support-set bottlenecks for video-text representation learning," 2020, arXiv (Cornell University)

Frequent co-authors who have collaborated with Florian Metze include:

  • Alan W. Black
  • Shinji Watanabe
  • Xinjian Li
  • Siddharth Dalmia
  • Po-Yao Huang

Best Publications

  • EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding

    Yajie Miao;Mohammad Gowayyed;Florian Metze

  • VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

    Hu Xu;Gargi Ghosh;Po-Yao Huang;Dmytro Okhonko

  • Extracting deep bottleneck features using stacked auto-encoders

    Jonas Gehring;Yajie Miao;Florian Metze;Alex Waibel

  • A one-pass decoder based on polymorphic linguistic context assignment

    H. Soltau;F. Metze;C. Fugen;A. Waibel

  • Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval

    Niluthpol Chowdhury Mithun;Juncheng Li;Florian Metze;Amit K. Roy-Chowdhury

  • Masked Autoencoders that Listen

    Unknown

  • How2: A Large-scale Dataset for Multimodal Language Understanding

    Ramon Sanabria;Ozan Caglayan;Shruti Palaskar;Desmond Elliott

  • Comparison of Four Approaches to Age and Gender Recognition for Telephone Applications

    F. Metze;J. Ajmera;R. Englert;U. Bub

  • Advances in automatic meeting record creation and access

    A. Waibel;M. Bett;F. Metze;K. Ries

  • A Comparison of Five Multiple Instance Learning Pooling Functions for Sound Event Detection with Weak Labeling

    Yun Wang;Juncheng Li;Florian Metze

  • How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language

    Amanda Duarte;Shruti Palaskar;Lucas Ventura;Deepti Ghadiyaram

  • A comparison of Deep Learning methods for environmental sound detection

    Juncheng Li;Wei Dai;Florian Metze;Shuhui Qu

  • Session independent non-audible speech recognition using surface electromyography

    L. Maier-Hein;F. Metze;T. Schultz;A. Waibel

  • A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition

    Aren Jansen;Emmanuel Dupoux;Sharon Goldwater;Mark Johnson

  • Support-set bottlenecks for video-text representation learning

    Mandela Patrick;Po-Yao Huang;Yuki Asano;Florian Metze

  • Deep maxout networks for low-resource speech recognition

    Yajie Miao;Florian Metze;Shourabh Rawat

  • Speaker adaptive training of deep neural network acoustic models using i-vectors

    Yajie Miao;Hao Zhang;Florian Metze

  • Anger recognition in speech using acoustic and linguistic cues

    Tim Polzehl;Alexander Schmitt;Florian Metze;Michael Wagner

  • A flexible stream architecture for ASR using articulatory features.

    Florian Metze;Alex Waibel

  • VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding

    Hu Xu;Gargi Ghosh;Po-Yao Huang;Prahal Arora

  • A Comparison of deep learning methods for environmental sound.

    Juncheng Li;Wei Dai;Florian Metze;Shuhui Qu

  • How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language

    Amanda Duarte;Shruti Palaskar;Deepti Ghadiyaram;Kenneth DeHaan

Frequent Co-Authors

Alex Waibel
Alex Waibel Carnegie Mellon University
Alan W. Black
Alan W. Black Carnegie Mellon University
Tanja Schultz
Tanja Schultz University of Bremen
Alexander G. Hauptmann
Alexander G. Hauptmann Carnegie Mellon University
Hagen Soltau
Hagen Soltau Google (United States)
Teruko Mitamura
Teruko Mitamura Carnegie Mellon University
Sebastian Möller
Sebastian Möller Technical University of Berlin
Xavier Anguera
Xavier Anguera ELSA Speak
Bhiksha Raj
Bhiksha Raj Carnegie Mellon University
Graham Neubig
Graham Neubig Carnegie Mellon University

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