H-Index & Metrics Best Publications
Nicholas Evans

Nicholas Evans

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 32 Citations 5,639 149 World Ranking 7423 National Ranking 188

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Spoofing attack, Computer security, Speaker verification, Biometrics and Speech recognition. His work deals with themes such as Cepstrum, Isolation, Speech synthesis and Word error rate, which intersect with Spoofing attack. His study in Computer security focuses on Replay attack in particular.

In his work, Nicholas Evans performs multidisciplinary research in Speaker verification and Countermeasure. With his scientific publications, his incorporates both Biometrics and Software deployment. His work on Speaker recognition as part of his general Speech recognition study is frequently connected to Constant, thereby bridging the divide between different branches of science.

His most cited work include:

  • Speaker Diarization: A Review of Recent Research (436 citations)
  • Spoofing and countermeasures for speaker verification (280 citations)
  • The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection (182 citations)

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

Speech recognition, Spoofing attack, Artificial intelligence, Speaker recognition and Biometrics are his primary areas of study. Speech recognition is frequently linked to Context in his study. His Spoofing attack research incorporates themes from Speaker verification, Replay attack and Speech synthesis.

His Speaker verification research includes themes of End-to-end principle and Anti spoofing. Nicholas Evans interconnects Natural language processing, Machine learning and Pattern recognition in the investigation of issues within Artificial intelligence. Nicholas Evans combines subjects such as Encryption, Database and Word error rate with his study of Biometrics.

He most often published in these fields:

  • Speech recognition (53.89%)
  • Spoofing attack (26.94%)
  • Artificial intelligence (25.91%)

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

  • Spoofing attack (26.94%)
  • Speech recognition (53.89%)
  • Biometrics (17.62%)

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

The scientist’s investigation covers issues in Spoofing attack, Speech recognition, Biometrics, Speech synthesis and Reliability. The study incorporates disciplines such as Speaker verification, Reliability and Artificial intelligence in addition to Spoofing attack. His biological study spans a wide range of topics, including Computer security, Machine learning and Anti spoofing.

His Speech recognition study typically links adjacent topics like Signal processing. The Biometrics study combines topics in areas such as Soundness, Feature vector and Spectrogram. His Speaker recognition research is multidisciplinary, incorporating elements of NIST, Training set and Encryption.

Between 2018 and 2021, his most popular works were:

  • ASVspoof 2019: Future horizons in spoofed and fake audio detection (88 citations)
  • Preserving privacy in speaker and speech characterisation (27 citations)
  • ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech (25 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Nicholas Evans spends much of his time researching Spoofing attack, Speech synthesis, Reliability, Physical access and Computer security. His Spoofing attack research incorporates elements of Machine learning, Feature extraction, Artificial intelligence, Word error rate and Voice presentation. His Speech synthesis research is included under the broader classification of Speech recognition.

His work on Utterance is typically connected to Constant as part of general Speech recognition study, connecting several disciplines of science. His studies examine the connections between Reliability and genetics, as well as such issues in Speaker verification, with regards to Artificial neural network, Ensemble learning, Fusion and SIMPLE. In the field of Computer security, his study on Replay attack and Data Protection Act 1998 overlaps with subjects such as Baseline.

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.

Best Publications

Speaker Diarization: A Review of Recent Research

Xavier Anguera Miro;S. Bozonnet;N. Evans;C. Fredouille.
IEEE Transactions on Audio, Speech, and Language Processing (2012)

632 Citations

Spoofing and countermeasures for speaker verification

Zhizheng Wu;Nicholas Evans;Tomi Kinnunen;Junichi Yamagishi.
Speech Communication (2015)

424 Citations

ASVspoof 2015: the First Automatic Speaker Verification Spoofing and Countermeasures Challenge

Zhizheng Wu;Tomi Kinnunen;Nicholas W. D. Evans;Junichi Yamagishi.
conference of the international speech communication association (2015)

292 Citations

A new feature for automatic speaker verification anti-spoofing: Constant Q cepstral coefficients

Massimiliano Todisco;Héctor Delgado;Nicholas W. D. Evans.
The Speaker and Language Recognition Workshop (Odyssey 2016) (2016)

259 Citations

The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection

Tomi Kinnunen;Md. Sahidullah;Héctor Delgado;Massimiliano Todisco.
conference of the international speech communication association (2017)

247 Citations

Constant Q cepstral coefficients

Massimiliano Todisco;Hctor Delgado;Nicholas Evans.
Computer Speech & Language (2017)

227 Citations

Spoofing and countermeasures for automatic speaker verification

Nicholas W. D. Evans;Tomi Kinnunen;Junichi Yamagishi.
conference of the international speech communication association (2013)

154 Citations

Biometrics systems under spoofing attack: an evaluation methodology and lessons learned

Abdenour Hadid;Nicholas W. D. Evans;Sébastien Marcel;Julian Fiérrez.
IEEE Signal Processing Magazine (2015)

152 Citations

ALIZE/SpkDet: a state-of-the-art open source software for speaker recognition

Jean-François Bonastre;Nicolas Scheffer;Driss Matrouf;Corinne Fredouille.
Odyssey 2008: The Speaker and Language Recognition Workshop (2008)

142 Citations

ASVspoof: The Automatic Speaker Verification Spoofing and Countermeasures Challenge

Zhizheng Wu;Junichi Yamagishi;Tomi Kinnunen;Cemal Hanilci.
IEEE Journal of Selected Topics in Signal Processing (2017)

122 Citations

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