The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Gilles Boulianne - One of the best experts on this subject based on the ideXlab platform.
-
language independent voice passphrase verification
International Conference on Acoustics Speech and Signal Processing, 2015Co-Authors: Gilles BoulianneAbstract:Voice passphrase verification is the task of deciding whether an audio recording contains a given passphrase. It is usually done by evaluating the likelihood of the passphrase reference text given the audio, which requires a different ASR system for each language. Here we look at verification when the passphrase reference is an audio recording instead of a text. We propose a decision likelihood ratio derived from a generative model. Training is unsupervised and needs only audio, without labelling, so the method applies to any language for which recorded audio exists. We report experiments on English and Urdu telephone speech, and show that our model-based likelihood ratio largely outperforms a baseline of DTW based on MFCC feature vectors.
-
ICASSP - Language-independent voice passphrase verification
2015 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2015Co-Authors: Gilles BoulianneAbstract:Voice passphrase verification is the task of deciding whether an audio recording contains a given passphrase. It is usually done by evaluating the likelihood of the passphrase reference text given the audio, which requires a different ASR system for each language. Here we look at verification when the passphrase reference is an audio recording instead of a text. We propose a decision likelihood ratio derived from a generative model. Training is unsupervised and needs only audio, without labelling, so the method applies to any language for which recorded audio exists. We report experiments on English and Urdu telephone speech, and show that our model-based likelihood ratio largely outperforms a baseline of DTW based on MFCC feature vectors.
Hagai Aronowitz - One of the best experts on this subject based on the ideXlab platform.
-
speaker recognition using common Passphrases in reddots
International Conference on Acoustics Speech and Signal Processing, 2017Co-Authors: Hagai AronowitzAbstract:In this paper we report our work on the recently collected text dependent speaker recognition dataset named RedDots, with a focus on the common passphrase condition. We first investigate an out-of-the-box approach. We then report several strategies to train on RedDots itself using up to 40 speakers for training. The GMM-NAP framework is used as a baseline. We report the following novelties: First, we demonstrate the use of bagging for improved accuracy. Second, we estimate the EER of a passphrase using metadata only. Third, the estimated EERs are used for improved score normalization. Finally we report an analysis of system sensitivity to the duration between enrollment and testing (template aging).
-
ICASSP - Speaker recognition using common Passphrases in RedDots
2017 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2017Co-Authors: Hagai AronowitzAbstract:In this paper we report our work on the recently collected text dependent speaker recognition dataset named RedDots, with a focus on the common passphrase condition. We first investigate an out-of-the-box approach. We then report several strategies to train on RedDots itself using up to 40 speakers for training. The GMM-NAP framework is used as a baseline. We report the following novelties: First, we demonstrate the use of bagging for improved accuracy. Second, we estimate the EER of a passphrase using metadata only. Third, the estimated EERs are used for improved score normalization. Finally we report an analysis of system sensitivity to the duration between enrollment and testing (template aging).
Vinnie Monaco - One of the best experts on this subject based on the ideXlab platform.
-
Using a predefined passphrase to evaluate a speaker verification system
Artificial Intelligence Research, 2014Co-Authors: Jonathan Leet, John Gibbons, Charles C. Tappert, Vinnie MonacoAbstract:This article presents a standardized and repeatable process used to evaluate the performance of a speaker verification system.Through the use of a common passphrase and a subset of extracted feature vectors that outperforms other combinations, thestudy limits the exposure to potential experimental flaws, while measuring true biometric performance more effectively thanexisting evaluation methodologies. After collecting a dataset of 33 participants, the researchers achieved a performance rate of99.8% for the 22 users who contributed at least 20 text-dependent samples. The primary focus of the research, however, was toillustrate a variety of testing techniques that can be used to efficiently analyze the performance of a speaker verification systemand advocate the use of a common passphrase in this process.
Ekaterina Shutova - One of the best experts on this subject based on the ideXlab platform.
-
Financial Cryptography Workshops - Linguistic properties of multi-word Passphrases
Financial Cryptography and Data Security, 2012Co-Authors: Joseph Bonneau, Ekaterina ShutovaAbstract:We examine patterns of human choice in a passphrase-based authentication system deployed by Amazon, a large online merchant. We tested the availability of a large corpus of over 100,000 possible phrases at Amazon's registration page, which prohibits using any phrase already registered by another user. A number of large, readily-available lists such as movie and book titles prove effective in guessing attacks, suggesting that Passphrases are vulnerable to dictionary attacks like all schemes involving human choice. Extending our analysis with natural language phrases extracted from linguistic corpora, we find that phrase selection is far from random, with users strongly preferring simple noun bigrams which are common in natural language. The distribution of chosen Passphrases is less skewed than the distribution of bigrams in English text, indicating that some users have attempted to choose phrases randomly. Still, the distribution of bigrams in natural language is not nearly random enough to resist offline guessing, nor are longer three- or four-word phrases for which we see rapidly diminishing returns.
-
Linguistic properties of multi-word Passphrases
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012Co-Authors: Joseph Bonneau, Ekaterina ShutovaAbstract:We examine patterns of human choice in a passphrase-based authentication system deployed by Amazon, a large online merchant. We tested the availability of a large corpus of over 100,000 possible phrases at Amazons registration page, which prohibits using any phrase already registered by another user. A number of large, readily-available lists such as movie and book titles prove effective in guessing attacks, suggesting that Passphrases are vulnerable to dictionary attacks like all schemes involving human choice. Extending our analysis with natural language phrases extracted from linguistic corpora, we find that phrase selection is far from random, with users strongly preferring simple noun bigrams which are common in natural language. The distribution of cho- sen Passphrases is less skewed than the distribution of bigrams in English text, indicating that some users have attempted to choose phrases ran- domly. Still, the distribution of bigrams in natural language is not nearly random enough to resist offline guessing, nor are longer three- or four- word phrases for which we see rapidly diminishing returns.
Miguel Vargas Martin - One of the best experts on this subject based on the ideXlab platform.
-
reinforcing system assigned Passphrases through implicit learning
Computer and Communications Security, 2018Co-Authors: Zeinab Joudaki, Julie Thorpe, Miguel Vargas MartinAbstract:People tend to choose short and predictable passwords that are vulnerable to guessing attacks. Passphrases are passwords consisting of multiple words, initially introduced as more secure authentication keys that people could recall. Unfortunately, people tend to choose predictable natural language patterns in Passphrases, again resulting in vulnerability to guessing attacks. One solution could be system-assigned Passphrases, but people have difficulty recalling them. With the goal of improving the usability of system-assigned Passphrases, we propose a new approach of reinforcing system-assigned Passphrases using implicit learning techniques. We design and test a system that implements this approach using two implicit learning techniques: contextual cueing and semantic priming. In a 780-participant online study, we explored the usability of 4-word system-assigned Passphrases using our system compared to a set of control conditions. Our study showed that our system significantly improves usability of system-assigned Passphrases, both in terms of recall rates and login time.
-
CCS - Reinforcing System-Assigned Passphrases Through Implicit Learning
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018Co-Authors: Zeinab Joudaki, Julie Thorpe, Miguel Vargas MartinAbstract:People tend to choose short and predictable passwords that are vulnerable to guessing attacks. Passphrases are passwords consisting of multiple words, initially introduced as more secure authentication keys that people could recall. Unfortunately, people tend to choose predictable natural language patterns in Passphrases, again resulting in vulnerability to guessing attacks. One solution could be system-assigned Passphrases, but people have difficulty recalling them. With the goal of improving the usability of system-assigned Passphrases, we propose a new approach of reinforcing system-assigned Passphrases using implicit learning techniques. We design and test a system that implements this approach using two implicit learning techniques: contextual cueing and semantic priming. In a 780-participant online study, we explored the usability of 4-word system-assigned Passphrases using our system compared to a set of control conditions. Our study showed that our system significantly improves usability of system-assigned Passphrases, both in terms of recall rates and login time.