Anderson Ávila

Assistant Professor in the department of Energy, Materials and Telecommunications at the Institut national de la recherche scientifique (INRS) and member of the INRS-UQO Joint Research Unit in Cybersecurity.

Research interests

Federated Learning for Data Privacy

Decentralization of artificial Intelligence models by enabling efficient training and inference on edge devices to foster data privacy

Cyber Defense and Human Language Processing

Combating misinformation from a range of semantic signals, including speech, text and image

Biometrics

Improving authentication by using physical and behavioural human traits

Research Interests

Areas for present and future researchs

Training openings

Training openings for students or interns

Biography

Biography and functions of Dr. Ávila

Publications

List of works publicated by Dr. Ávila

Contact

Dr. Ávila contact information

Training openings for students or interns

Projects carried out with the financial support of:

Biography and Functions

Dr. Anderson Avila is an Assistant Professor at INRS-EMT, working in the INRS-UQO Joint Research Unit in Cybersecurity. His research background is on machine learning and signal processing applied to natural language processing. During his PhD, Dr. Avila worked on the development of new models for speech quality assessment and on the robustness of voice biometrics.

Prior to joining INRS-UQO, Dr. Avila was a researcher scientist in natural language and speech processing, working on projects related to model compression, low-latency and robustness of spoken language understanding.

Dr. Avila received his BSc in Computer Science from the Federal University of São Carlos, his MSc from Federal University of ABC and his PhD from INRS.

Publications

Avila, D. O’Shaughnessy, T. Falk, Automatic Speaker Verification from Affective Speech Using Gaussian Mixture Model Based Estimation of Neutral Speech Characteristics, J. Speech Communication, vol. 132, p. 21-31, 2021.

A. Avila, J. Alam, F. Prado, D. O’Shaughnessy, T. Falk, On the Use of Blind Channel Response Estimation and a Residual Neural Network to Detect Physical Access Attacks to Speaker Verification Systems, J. Computer Speech & Language, vol. 66, 2021.

A. Avila, D. O’Shaughnessy, T. Falk, Non-intrusive Speech Quality Prediction Based on the Blind Estimation of Clean Speech and the i-vector Framework, J. Quality and User Experience, vol.5, no 1, p. 1-15, 2020.

A. Avila, J. Alam, D. O’Shaughnessy, T. Falk, On the Use of the I-vector Speech Representation for Instrumental Quality Measurement, J. Quality and User Experience, 2020, vol. 5, no 1, pp. 1-14, DOI.

Contact

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