Search Results for author: Massimiliano Todisco

Found 29 papers, 14 papers with code

On the potential of jointly-optimised solutions to spoofing attack detection and automatic speaker verification

no code implementations1 Sep 2022 Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans

The spoofing-aware speaker verification (SASV) challenge was designed to promote the study of jointly-optimised solutions to accomplish the traditionally separately-optimised tasks of spoofing detection and speaker verification.

Speaker Verification

The VoicePrivacy 2020 Challenge Evaluation Plan

1 code implementation14 May 2022 Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco

The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.

The VoicePrivacy 2022 Challenge Evaluation Plan

1 code implementation23 Mar 2022 Natalia Tomashenko, Xin Wang, Xiaoxiao Miao, Hubert Nourtel, Pierre Champion, Massimiliano Todisco, Emmanuel Vincent, Nicholas Evans, Junichi Yamagishi, Jean-François Bonastre

Participants apply their developed anonymization systems, run evaluation scripts and submit objective evaluation results and anonymized speech data to the organizers.

Speaker Verification

Explainable deepfake and spoofing detection: an attack analysis using SHapley Additive exPlanations

1 code implementation28 Feb 2022 Wanying Ge, Massimiliano Todisco, Nicholas Evans

Despite several years of research in deepfake and spoofing detection for automatic speaker verification, little is known about the artefacts that classifiers use to distinguish between bona fide and spoofed utterances.

Face Swapping Speaker Verification

RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofing

1 code implementation8 Nov 2021 Hemlata Tak, Madhu Kamble, Jose Patino, Massimiliano Todisco, Nicholas Evans

This paper introduces RawBoost, a data boosting and augmentation method for the design of more reliable spoofing detection solutions which operate directly upon raw waveform inputs.

Speaker Verification Voice Anti-spoofing

ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan

no code implementations1 Sep 2021 Héctor Delgado, Nicholas Evans, Tomi Kinnunen, Kong Aik Lee, Xuechen Liu, Andreas Nautsch, Jose Patino, Md Sahidullah, Massimiliano Todisco, Xin Wang, Junichi Yamagishi

The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and the development of countermeasures.

Face Swapping Speaker Verification

ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection

no code implementations1 Sep 2021 Junichi Yamagishi, Xin Wang, Massimiliano Todisco, Md Sahidullah, Jose Patino, Andreas Nautsch, Xuechen Liu, Kong Aik Lee, Tomi Kinnunen, Nicholas Evans, Héctor Delgado

In addition to a continued focus upon logical and physical access tasks in which there are a number of advances compared to previous editions, ASVspoof 2021 introduces a new task involving deepfake speech detection.

Face Swapping Speaker Verification

Raw Differentiable Architecture Search for Speech Deepfake and Spoofing Detection

1 code implementation26 Jul 2021 Wanying Ge, Jose Patino, Massimiliano Todisco, Nicholas Evans

End-to-end approaches to anti-spoofing, especially those which operate directly upon the raw signal, are starting to be competitive with their more traditional counterparts.

Face Swapping

Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing

1 code implementation11 Jun 2021 Tomi Kinnunen, Andreas Nautsch, Md Sahidullah, Nicholas Evans, Xin Wang, Massimiliano Todisco, Héctor Delgado, Junichi Yamagishi, Kong Aik Lee

Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behaviour, (dis)similarity or complementarity.

Speaker Verification Voice Anti-spoofing

Graph Attention Networks for Anti-Spoofing

no code implementations8 Apr 2021 Hemlata Tak, Jee-weon Jung, Jose Patino, Massimiliano Todisco, Nicholas Evans

This paper reports our use of graph attention networks (GATs) to model these relationships and to improve spoofing detection performance.

Graph Attention Speaker Verification

Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection

1 code implementation7 Apr 2021 Wanying Ge, Michele Panariello, Jose Patino, Massimiliano Todisco, Nicholas Evans

This paper reports the first successful application of a differentiable architecture search (DARTS) approach to the deepfake and spoofing detection problems.

Face Swapping Neural Architecture Search

Speaker anonymisation using the McAdams coefficient

1 code implementation2 Nov 2020 Jose Patino, Natalia Tomashenko, Massimiliano Todisco, Andreas Nautsch, Nicholas Evans

Anonymisation has the goal of manipulating speech signals in order to degrade the reliability of automatic approaches to speaker recognition, while preserving other aspects of speech, such as those relating to intelligibility and naturalness.

Speaker Recognition

End-to-end anti-spoofing with RawNet2

1 code implementation2 Nov 2020 Hemlata Tak, Jose Patino, Massimiliano Todisco, Andreas Nautsch, Nicholas Evans, Anthony Larcher

Spoofing countermeasures aim to protect automatic speaker verification systems from attempts to manipulate their reliability with the use of spoofed speech signals.

Speaker Verification

Texture-based Presentation Attack Detection for Automatic Speaker Verification

no code implementations8 Oct 2020 Lazaro J. Gonzalez-Soler, Jose Patino, Marta Gomez-Barrero, Massimiliano Todisco, Christoph Busch, Nicholas Evans

Despite these and other advantages, biometric systems in general and Automatic speaker verification (ASV) systems in particular can be vulnerable to attack presentations.

Speaker Verification

Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals

no code implementations12 Jul 2020 Tomi Kinnunen, Héctor Delgado, Nicholas Evans, Kong Aik Lee, Ville Vestman, Andreas Nautsch, Massimiliano Todisco, Xin Wang, Md Sahidullah, Junichi Yamagishi, Douglas A. Reynolds

Recent years have seen growing efforts to develop spoofing countermeasures (CMs) to protect automatic speaker verification (ASV) systems from being deceived by manipulated or artificial inputs.

Speaker Verification

The Privacy ZEBRA: Zero Evidence Biometric Recognition Assessment

2 code implementations19 May 2020 Andreas Nautsch, Jose Patino, Natalia Tomashenko, Junichi Yamagishi, Paul-Gauthier Noe, Jean-Francois Bonastre, Massimiliano Todisco, Nicholas Evans

Mounting privacy legislation calls for the preservation of privacy in speech technology, though solutions are gravely lacking.

Cryptography and Security Audio and Speech Processing

Introducing the VoicePrivacy Initiative

3 code implementations4 May 2020 Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco

The VoicePrivacy initiative aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.

Introduction to Voice Presentation Attack Detection and Recent Advances

no code implementations4 Jan 2019 Md Sahidullah, Hector Delgado, Massimiliano Todisco, Tomi Kinnunen, Nicholas Evans, Junichi Yamagishi, Kong-Aik Lee

Over the past few years significant progress has been made in the field of presentation attack detection (PAD) for automatic speaker recognition (ASV).

Speaker Recognition

EMOVO Corpus: an Italian Emotional Speech Database

no code implementations LREC 2014 Giovanni Costantini, Iacopo Iaderola, Andrea Paoloni, Massimiliano Todisco

It is observed that emotions less easy to recognize are joy and disgust, whereas the most easy to detect are anger, sadness and the neutral state.

Speech Emotion Recognition

Intelligibility assessment in forensic applications

no code implementations LREC 2012 Giovanni Costantini, Andrea Paoloni, Massimiliano Todisco

In the absence of the original signal, the only way to see the level of accuracy that can be obtained in the transcription of poor recordings is to develop an objective methodology for intelligibility measurements.

Speech Enhancement

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