User’s Guide¶
This package contains access API and description of the voicePA database interface. It includes Bob-compliant methods for using the database directly from python with provided protocols.
Genuine data¶
The genuine (non-attack) data is taken directly from AVspoof database and can be used by both automatic speaker verification (ASV) and presentation attack detection (PAD) systems. The genuine data acquisition process lasted approximately two months with 44 subjects, each participating in four different sessions configured in different environmental setups. During each recording session, subjects were asked to speak out prepared (read) speech, pass-phrases and free speech recorded with three devices: one laptop with high-quality microphone and two mobile phones (iPhone 3GS and Samsung S3).
Attack data¶
Based on the genuine data, 24 types of presentation attacks were generated. Attacks were recorded in 3 different environments (two typical offices and a large conference room), using 5 different playback devices, including built-in laptop speakers, high quality speakers, and three phones: iPhone 3GS, iPhone 6S, and Samsung S3, and assuming an ASV system running on either laptop, iPhone 3GS, or Samsung S3. In addition to a replay type of attacks (speech is recorded and replayed to the microphone of an ASV system), two types of synthetic speech were also replayed: speech synthesis and voice conversion (for the details on these algorithms, please refer to the paper below published in BTAS 2015 and describing AVspoof database).
Here is the list of all attacks in voicePA database:
r106-iphone3gs-laptop-iphone6s
r106-iphone3gs-samsungs3-samsungs3
r106-iphone3gs-ss-iphone6s
r106-iphone3gs-vc-iphone6s
r106-samsungs3-iphone3gs-iphone3gs
r106-samsungs3-laptop-iphone6s
r106-samsungs3-ss-iphone6s
r106-samsungs3-vc-iphone6s
r107-laptop-iphone3gs-iphone3gs
r107-laptop-laptop-hqspeaker
r107-laptop-laptop-laptop
r107-laptop-samsungs3-samsungs3
r107-laptop-ss-hqspeaker
r107-laptop-ss-laptop
r107-laptop-vc-hqspeaker
r107-laptop-vc-laptop
seboffice-iphone3gs-laptop-iphone6s
seboffice-iphone3gs-samsungs3-samsungs3
seboffice-iphone3gs-ss-iphone6s
seboffice-iphone3gs-vc-iphone6s
seboffice-samsungs3-iphone3gs-iphone3gs
seboffice-samsungs3-laptop-iphone6s
seboffice-samsungs3-ss-iphone6s
seboffice-samsungs3-vc-iphone6s
The names of these attacks can be interpreted as following: [environment name]-[devices where ASV system is running]-[type of attack data]-[device of the attack].
Environment represents the place where the attacks were recorded and includes:
r106 - a large conference room with echo and constant background noise from air-conditioning unit.
r107 - a small corner office
seboffice - a larger office with background noise from the wind outside, occasional cars and birds.
Devices where ASV was running are:
laptop - all the attacks recorded with laptop are copied directly from AVspoof database and correspond
to replay and physical access attacks in AVspoof.
iphone3gs - an ASV system is assumed to be running on iPhone 3GS, it means the standard microphone of
the iPhone 3GS is used to record attacks.
samsungs3 - similar to the above, attacks are recorded using microphone of Samsung S3 phone.
Type of attack data include:
replay attacks - created by playing back either the data recorded with 'laptop' or both 'iphone3gs' and 'samsungs3' phones.
ss - data generated with speech synthesis algorithm
vc - data generated with voice conversion algorithm
The attacks devices that are used to play back the attack data:
laptop - internal speakers of the laptop (see 'replay_laptop' and 'physical_access' attacks from AVspoof database)
hqspeaker - high quality speakers connected to the laptop (see 'replay_laptop_HQ' and 'physical_access_HQ'
attacks from AVspoof database)
iphone3gs - iPhone 3GS was used to playback the data.
samsungs3 - Samsung S3 was used to playback the data.
iphone6s - iPhone 6S was used to playback the data.
Protocols¶
The data in voicePA database is split into three non-overlapping subsets: training (genuine and attack samples from 4 female and 4 male subjects), development or ‘Dev’ (genuine and attack samples from 4 female and 10 male subjects), and evaluation or ‘Eval’ (genuine and attack samples from 5 female and 11 male subjects).
- Within these train, dev, and eval sets, the following protocols are provided:
‘grandtest’ - all genuine and attack data are included in this protocol. ‘smalltest’ - a small subset of genuine and attack data (only one subject for each train, dev, and eval sets). This protocol should be used for debugging purposes only. ‘avspoofPA’ - this protocol includes all genuine data and the presentation attack data from AVspoof database (corresponding to ‘physical_access’ attacks). ‘r106’ - all genuine data and all attacks recorded in the large conference room. ‘seboffice’ - all genuine data and all attacks recorded in the office room. ‘replay’ - all genuine and replay attacks of natural speech (no ‘ss’ and ‘vc’ data). ‘synthetic’ - all genuine and synthetic speech only (‘ss’ and ‘vc’ data), hence no replay attacks of a natural speech. ‘mobile’ - all genuine and attacks on ASV systems running on mobile devices, which means target devices are iPhone 3GS and Samsung S3. ‘samsungs3’ - all genuine and attacks only for Samsung S3 device (ASV system is assumed to be running on this device only). ‘iphone3gs’ - all genuine and attacks only for iPhone 3GS device (ASV system is assumed to be running on this device only).