H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 39 Citations 6,726 235 World Ranking 4815 National Ranking 2388

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Speech recognition
  • Machine learning

His primary scientific interests are in Artificial intelligence, Speech recognition, Natural language processing, Pattern recognition and Feature. His work in Artificial intelligence covers topics such as Machine learning which are related to areas like Text retrieval. The concepts of his Speech recognition study are interwoven with issues in Recurrent neural network, Feature extraction and Word.

His biological study spans a wide range of topics, including The Internet and Zero. Event is closely connected to Time delay neural network in his research, which is encompassed under the umbrella topic of Pattern recognition. He interconnects Speaker recognition and Training set in the investigation of issues within Feature.

His most cited work include:

  • EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding (360 citations)
  • Extracting deep bottleneck features using stacked auto-encoders (189 citations)
  • A one-pass decoder based on polymorphic linguistic context assignment (175 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Speech recognition, Artificial intelligence, Natural language processing, Word and Word error rate. He has included themes like Context, Feature extraction and Feature in his Speech recognition study. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Vocabulary and Pattern recognition.

His study in Natural language processing is interdisciplinary in nature, drawing from both Speech corpus and Utterance. His Word research is multidisciplinary, relying on both Sentence and Connectionism. His studies deal with areas such as Training set and Adaptation as well as Word error rate.

He most often published in these fields:

  • Speech recognition (53.80%)
  • Artificial intelligence (45.54%)
  • Natural language processing (28.38%)

What were the highlights of his more recent work (between 2018-2021)?

  • Speech recognition (53.80%)
  • Artificial intelligence (45.54%)
  • Natural language processing (28.38%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Speech recognition, Artificial intelligence, Natural language processing, Word and Context. Florian Metze specializes in Speech recognition, namely Word error rate. His Word error rate research includes elements of Variety, Artificial neural network, Inuktitut, Acoustic model and Joint.

His Artificial intelligence research includes themes of Machine learning and Pattern recognition. His work on Text processing as part of general Natural language processing study is frequently connected to Modalities, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Word study combines topics in areas such as Adversarial system, Embedding, Adversary, Sentence and Construct.

Between 2018 and 2021, his most popular works were:

  • A Comparison of Five Multiple Instance Learning Pooling Functions for Sound Event Detection with Weak Labeling (56 citations)
  • Effective Dimensionality Reduction for Word Embeddings. (33 citations)
  • Multimodal Abstractive Summarization for How2 Videos (20 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Speech recognition

His primary areas of study are Speech recognition, Artificial intelligence, Word error rate, Word and Artificial neural network. The Speech recognition study combines topics in areas such as Domain, Inference, Multimodal learning, Transcription and Robustness. His work carried out in the field of Artificial intelligence brings together such families of science as Pattern recognition and Natural language processing.

His Word error rate study also includes fields such as

  • Context which is related to area like End-to-end principle, Convolutional neural network, Feature extraction, Adaptation and Pipeline,
  • Acoustic model which intersects with area such as Vowel, Consonant, Language documentation, Pronunciation and Language model. He has researched Word in several fields, including Adversarial system, Adversary, Construct and Sentence. His work is dedicated to discovering how Artificial neural network, Representation are connected with Benchmark, Machine learning and Sensory cue and other disciplines.

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.

Top Publications

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

Yajie Miao;Mohammad Gowayyed;Florian Metze.
ieee automatic speech recognition and understanding workshop (2015)

479 Citations

Extracting deep bottleneck features using stacked auto-encoders

Jonas Gehring;Yajie Miao;Florian Metze;Alex Waibel.
international conference on acoustics, speech, and signal processing (2013)

278 Citations

A one-pass decoder based on polymorphic linguistic context assignment

H. Soltau;F. Metze;C. Fugen;A. Waibel.
ieee automatic speech recognition and understanding workshop (2001)

247 Citations

Advances in automatic meeting record creation and access

A. Waibel;M. Bett;F. Metze;K. Ries.
international conference on acoustics, speech, and signal processing (2001)

179 Citations

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

F. Metze;J. Ajmera;R. Englert;U. Bub.
international conference on acoustics, speech, and signal processing (2007)

174 Citations

Session independent non-audible speech recognition using surface electromyography

L. Maier-Hein;F. Metze;T. Schultz;A. Waibel.
ieee automatic speech recognition and understanding workshop (2005)

139 Citations

A flexible stream architecture for ASR using articulatory features.

Florian Metze;Alex Waibel.
conference of the international speech communication association (2002)

113 Citations

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

Yajie Miao;Hao Zhang;Florian Metze.
IEEE Transactions on Audio, Speech, and Language Processing (2015)

108 Citations

Deep maxout networks for low-resource speech recognition

Yajie Miao;Florian Metze;Shourabh Rawat.
ieee automatic speech recognition and understanding workshop (2013)

103 Citations

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.
international conference on acoustics, speech, and signal processing (2013)

101 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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