diff --git a/advanced/databases/avspoof/5.json b/advanced/databases/avspoof/5.json
new file mode 100644
index 0000000000000000000000000000000000000000..7009832e4407d30dfccace1062a2894ded3aa933
--- /dev/null
+++ b/advanced/databases/avspoof/5.json
@@ -0,0 +1,503 @@
+{
+ "description": "The AVspoof Database",
+ "root_folder": "/idiap/resource/database/AVSpoof",
+ "protocols": [
+ {
+ "name": "smalltest_verify_train",
+ "template": "verify_trainset_speech/1",
+ "views": {
+ "train_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "train",
+ "protocol": "smalltest",
+ "purpose": "enroll"
+ }
+ },
+ "train_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "train",
+ "protocol": "smalltest"
+ }
+ }
+ }
+ },
+ {
+ "name": "smalltest_verify_train_spoof",
+ "template": "verify_trainset_speech_spoof/1",
+ "views": {
+ "train_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "train",
+ "protocol": "smalltest"
+ }
+ }
+ }
+ },
+ {
+ "name": "smalltest_verification",
+ "template": "advanced_speaker_recognition/1",
+ "views": {
+ "train": {
+ "view": "RecognitionTraining",
+ "parameters": {
+ "group": "train",
+ "protocol": "smalltest"
+ }
+ },
+ "dev_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "devel",
+ "protocol": "smalltest",
+ "purpose": "enroll"
+ }
+ },
+ "dev_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "devel",
+ "protocol": "smalltest"
+ }
+ },
+ "test_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "test",
+ "protocol": "smalltest",
+ "purpose": "enroll"
+ }
+ },
+ "test_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "test",
+ "protocol": "smalltest"
+ }
+ }
+ }
+ },
+ {
+ "name": "smalltest_verification_spoof",
+ "template": "speaker_recognition_spoof/1",
+ "views": {
+ "dev_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "devel",
+ "protocol": "smalltest"
+ }
+ },
+ "test_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "test",
+ "protocol": "smalltest"
+ }
+ }
+ }
+ },
+ {
+ "name": "grandtest_verify_train",
+ "template": "verify_trainset_speech/1",
+ "views": {
+ "train_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "train",
+ "protocol": "grandtest",
+ "purpose": "enroll"
+ }
+ },
+ "train_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "train",
+ "protocol": "grandtest"
+ }
+ }
+ }
+ },
+ {
+ "name": "grandtest_verify_train_spoof",
+ "template": "verify_trainset_speech_spoof/1",
+ "views": {
+ "train_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "train",
+ "protocol": "grandtest"
+ }
+ }
+ }
+ },
+ {
+ "name": "grandtest_verification",
+ "template": "advanced_speaker_recognition/1",
+ "views": {
+ "train": {
+ "view": "RecognitionTraining",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "train"
+ }
+ },
+ "dev_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "grandtest",
+ "purpose": "enroll",
+ "group": "devel"
+ }
+ },
+ "dev_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "devel"
+ }
+ },
+ "test_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "grandtest",
+ "purpose": "enroll",
+ "group": "test"
+ }
+ },
+ "test_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "grandtest_verification_spoof",
+ "template": "speaker_recognition_spoof/1",
+ "views": {
+ "dev_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "devel"
+ }
+ },
+ "test_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "physicalaccess_verify_train",
+ "template": "verify_trainset_speech/1",
+ "views": {
+ "train_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "train",
+ "protocol": "physical_access",
+ "purpose": "enroll"
+ }
+ },
+ "train_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "train",
+ "protocol": "physical_access"
+ }
+ }
+ }
+ },
+ {
+ "name": "physicalaccess_verify_train_spoof",
+ "template": "verify_trainset_speech_spoof/1",
+ "views": {
+ "train_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "train",
+ "protocol": "physical_access"
+ }
+ }
+ }
+ },
+ {
+ "name": "physicalaccess_verification",
+ "template": "advanced_speaker_recognition/1",
+ "views": {
+ "train": {
+ "view": "RecognitionTraining",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "train"
+ }
+ },
+ "dev_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "physical_access",
+ "purpose": "enroll",
+ "group": "devel"
+ }
+ },
+ "dev_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "devel"
+ }
+ },
+ "test_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "physical_access",
+ "purpose": "enroll",
+ "group": "test"
+ }
+ },
+ "test_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "physicalaccess_verification_spoof",
+ "template": "speaker_recognition_spoof/1",
+ "views": {
+ "dev_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "devel"
+ }
+ },
+ "test_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "logicalaccess_verify_train",
+ "template": "verify_trainset_speech/1",
+ "views": {
+ "train_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "group": "train",
+ "protocol": "logical_access",
+ "purpose": "enroll"
+ }
+ },
+ "train_probes": {
+ "view": "Probes",
+ "parameters": {
+ "group": "train",
+ "protocol": "logical_access"
+ }
+ }
+ }
+ },
+ {
+ "name": "logicalaccess_verify_train_spoof",
+ "template": "verify_trainset_speech_spoof/1",
+ "views": {
+ "train_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "group": "train",
+ "protocol": "logical_access"
+ }
+ }
+ }
+ },
+ {
+ "name": "logicalaccess_verification",
+ "template": "advanced_speaker_recognition/1",
+ "views": {
+ "train": {
+ "view": "RecognitionTraining",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "train"
+ }
+ },
+ "dev_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "logical_access",
+ "purpose": "enroll",
+ "group": "devel"
+ }
+ },
+ "dev_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "devel"
+ }
+ },
+ "test_templates": {
+ "view": "RecognitionTemplates",
+ "parameters": {
+ "protocol": "logical_access",
+ "purpose": "enroll",
+ "group": "test"
+ }
+ },
+ "test_probes": {
+ "view": "Probes",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "logicalaccess_verification_spoof",
+ "template": "speaker_recognition_spoof/1",
+ "views": {
+ "dev_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "devel"
+ }
+ },
+ "test_attacks": {
+ "view": "Attacks",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "smalltest_antispoofing",
+ "template": "simple_speech_antispoofing/1",
+ "views": {
+ "train": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "group": "train",
+ "protocol": "smalltest"
+ }
+ },
+ "dev_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "group": "devel",
+ "protocol": "smalltest"
+ }
+ },
+ "eval_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "group": "test",
+ "protocol": "smalltest"
+ }
+ }
+ }
+ },
+ {
+ "name": "grandtest_antispoofing",
+ "template": "simple_speech_antispoofing/1",
+ "views": {
+ "train": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "train"
+ }
+ },
+ "dev_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "devel"
+ }
+ },
+ "eval_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "grandtest",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "physicalaccess_antispoofing",
+ "template": "simple_speech_antispoofing/1",
+ "views": {
+ "train": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "train"
+ }
+ },
+ "dev_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "devel"
+ }
+ },
+ "eval_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "physical_access",
+ "group": "test"
+ }
+ }
+ }
+ },
+ {
+ "name": "logicalaccess_antispoofing",
+ "template": "simple_speech_antispoofing/1",
+ "views": {
+ "train": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "train"
+ }
+ },
+ "dev_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "devel"
+ }
+ },
+ "eval_probes": {
+ "view": "SimpleAntispoofing",
+ "parameters": {
+ "protocol": "logical_access",
+ "group": "test"
+ }
+ }
+ }
+ }
+ ],
+ "schema_version": 2
+}
\ No newline at end of file
diff --git a/advanced/databases/avspoof/5.py b/advanced/databases/avspoof/5.py
new file mode 100644
index 0000000000000000000000000000000000000000..d39daa24ae31bcc21af39204d7083ab9ac38844b
--- /dev/null
+++ b/advanced/databases/avspoof/5.py
@@ -0,0 +1,539 @@
+###############################################################################
+# #
+# Copyright (c) 2018 Idiap Research Institute, http://www.idiap.ch/ #
+# Contact: beat.support@idiap.ch #
+# #
+# This file is part of the beat.examples module of the BEAT platform. #
+# #
+# Commercial License Usage #
+# Licensees holding valid commercial BEAT licenses may use this file in #
+# accordance with the terms contained in a written agreement between you #
+# and Idiap. For further information contact tto@idiap.ch #
+# #
+# Alternatively, this file may be used under the terms of the GNU Affero #
+# Public License version 3 as published by the Free Software and appearing #
+# in the file LICENSE.AGPL included in the packaging of this file. #
+# The BEAT platform is distributed in the hope that it will be useful, but #
+# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY #
+# or FITNESS FOR A PARTICULAR PURPOSE. #
+# #
+# You should have received a copy of the GNU Affero Public License along #
+# with the BEAT platform. If not, see http://www.gnu.org/licenses/. #
+# #
+###############################################################################
+
+import numpy as np
+from collections import namedtuple
+
+from beat.backend.python.database import View
+
+import bob.io.base
+import bob.db.avspoof
+import scipy.io.wavfile
+
+from bob.db.avspoof.driver import Interface
+
+INFO = Interface()
+SQLITE_FILE = INFO.files()[0]
+
+
+#----------------------------------------------------------
+
+
+class RecognitionTraining(View):
+ """Outputs:
+ - speech: "{{ system_user.username }}/array_1d_floats/1"
+ - file_id: "{{ system_user.username }}/text/1"
+ - client_id: "{{ system_user.username }}/text/1"
+
+ One "file_id" is associated with a given "speech".
+ Several "speech" are associated with a given "client_id".
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | speech | | speech | | speech | | speech | | speech | | speech |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | file_id | | file_id | | file_id | | file_id | | file_id | | file_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | client_id | | client_id |
+ ----------------------------------------------- -----------------------------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'file_id', 'speech'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.avspoof.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=parameters['group'],
+ cls=('enroll', 'probe')),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry(x.client_id, x.id, x.make_path(root_folder, '.wav')) for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'text': str(obj.client_id)
+ }
+
+ elif output == 'file_id':
+ return {
+ 'text': str(obj.file_id)
+ }
+
+ elif output == 'speech':
+ rate, audio = scipy.io.wavfile.read(obj.speech)
+
+ return {
+ 'value': np.cast['float'](audio)
+ }
+
+
+#----------------------------------------------------------
+
+
+class RecognitionTemplates(View):
+ """Outputs:
+ - speech: "{{ system_user.username }}/array_1d_floats/1"
+ - file_id: "{{ system_user.username }}/text/1"
+ - template_id: "{{ system_user.username }}/text/1"
+ - client_id: "{{ system_user.username }}/text/1"
+
+ One "file_id" is associated with a given "speech".
+ Several "speech" are associated with a given "template_id".
+ Several "template_id" are associated with a given "client_id".
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | speech | | speech | | speech | | speech | | speech | | speech |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | file_id | | file_id | | file_id | | file_id | | file_id | | file_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | template_id | | template_id |
+ ----------------------------------------------- -----------------------------------------------
+ -----------------------------------------------------------------------------------------------
+ | client_id |
+ -----------------------------------------------------------------------------------------------
+
+ Note: for this particular database, there is only one "template_id"
+ per "client_id".
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['client_id', 'template_id', 'file_id', 'speech'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.avspoof.Database()
+
+ if parameters['protocol'] == "smalltest":
+ if parameters['group'] == "train":
+ template_ids = sorted([1, 3])
+ if parameters['group'] == "devel":
+ template_ids = sorted([15, 20])
+ if parameters['group'] == "test":
+ template_ids = sorted([18, 33])
+ else:
+ template_ids = [ client.id for client in db.clients(groups=parameters['group']) ]
+
+ entries = []
+
+ for template_id in template_ids:
+ objs = db.objects(groups=parameters['group'],
+ protocol=parameters['protocol'],
+ cls=parameters['purpose'],
+ clients=(template_id,))
+
+ entries.extend([ Entry(x.client_id, template_id, x.id, x.make_path(root_folder, '.wav'))
+ for x in objs ])
+
+ return sorted(entries, key=lambda x: (x.client_id, x.template_id, x.file_id))
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'client_id':
+ return {
+ 'text': str(obj.client_id)
+ }
+
+ elif output == 'template_id':
+ return {
+ 'text': str(obj.template_id)
+ }
+
+ elif output == 'file_id':
+ return {
+ 'text': str(obj.file_id)
+ }
+
+ elif output == 'speech':
+ rate, audio = scipy.io.wavfile.read(obj.speech)
+
+ return {
+ 'value': np.cast['float'](audio)
+ }
+
+
+#----------------------------------------------------------
+
+
+class Probes(View):
+ """Outputs:
+ - speech: "{{ system_user.username }}/array_1d_floats/1"
+ - file_id: "{{ system_user.username }}/text/1"
+ - probe_id: "{{ system_user.username }}/text/1",
+ - client_id: "{{ system_user.username }}/text/1"
+ - template_ids: "{{ system_user.username }}/array_1d_text/1",
+
+ One "file_id" is associated with a given "speech".
+ One "probe_id" is associated with a given "speech".
+ Several "speech" are associated with a given "client_id".
+ Several "client_id" are associated with a given "template_ids".
+
+ Each probe must be matched against a number of templates defined by a list of
+ client identifiers.
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | speech | | speech | | speech | | speech | | speech | | speech |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | file_id | | file_id | | file_id | | file_id | | file_id | | file_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | probe_id | | probe_id | | probe_id | | probe_id | | probe_id | | probe_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | client_id | | client_id |
+ ----------------------------------------------- -----------------------------------------------
+ -----------------------------------------------------------------------------------------------
+ | template_ids |
+ -----------------------------------------------------------------------------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['template_ids', 'client_id', 'probe_id', 'file_id', 'speech'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.avspoof.Database()
+
+ if parameters['protocol'] == "smalltest":
+ if parameters['group'] == "train":
+ template_ids = sorted([1, 3])
+ if parameters['group'] == "devel":
+ template_ids = sorted([15, 20])
+ if parameters['group'] == "test":
+ template_ids = sorted([18, 33])
+ else:
+ template_ids = sorted([ client.id for client in db.clients(groups=parameters['group']) ])
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=parameters['group'],
+ cls='probe'),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry(template_ids, x.client_id, x.id, x.id, x.make_path(root_folder, '.wav')) for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'template_ids':
+ return {
+ 'text': [ str(x) for x in obj.template_ids ]
+ }
+
+ elif output == 'client_id':
+ return {
+ 'text': str(obj.client_id)
+ }
+
+ elif output == 'probe_id':
+ return {
+ 'text': str(obj.probe_id)
+ }
+
+ elif output == 'file_id':
+ return {
+ 'text': str(obj.file_id)
+ }
+
+ elif output == 'speech':
+ rate, audio = scipy.io.wavfile.read(obj.speech)
+
+ return {
+ 'value': np.cast['float'](audio)
+ }
+
+
+#----------------------------------------------------------
+
+
+class Attacks(View):
+ """Outputs:
+ - speech: "{{ system_user.username }}/array_1d_floats/1"
+ - file_id: "{{ system_user.username }}/text/1"
+ - attack_id: "{{ system_user.username }}/text/1",
+ - client_id: "{{ system_user.username }}/text/1"
+ - template_ids: "{{ system_user.username }}/array_1d_text/1",
+
+ One "file_id" is associated with a given "speech".
+ One "probe_id" is associated with a given "speech".
+ Several "speech" are associated with a given "client_id".
+ Several "client_id" are associated with a given "template_ids".
+
+ Each probe must be matched against a number of templates defined by a list of
+ client identifiers.
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | speech | | speech | | speech | | speech | | speech | | speech |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | file_id | | file_id | | file_id | | file_id | | file_id | | file_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | attack_id | | attack_id | | attack_id | | attack_id | | attack_id | | attack_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ----------------------------------------------- -----------------------------------------------
+ | client_id | | client_id |
+ ----------------------------------------------- -----------------------------------------------
+ -----------------------------------------------------------------------------------------------
+ | template_ids |
+ -----------------------------------------------------------------------------------------------
+ """
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['template_ids', 'client_id', 'attack_id', 'file_id', 'speech'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.avspoof.Database()
+
+ objs = sorted(db.objects(protocol=parameters['protocol'],
+ groups=parameters['group'],
+ cls='attack'),
+ key=lambda x: (x.client_id, x.id))
+
+ return [ Entry([ str(x.client_id) ], x.client_id, x.id, x.id,
+ x.make_path(root_folder, '.wav')) for x in objs ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'template_ids':
+ return {
+ 'text': obj.template_ids
+ }
+
+ elif output == 'client_id':
+ return {
+ 'text': str(obj.client_id)
+ }
+
+ elif output == 'attack_id':
+ return {
+ 'text': str(obj.attack_id)
+ }
+
+ elif output == 'file_id':
+ return {
+ 'text': str(obj.file_id)
+ }
+
+ elif output == 'speech':
+ rate, audio = scipy.io.wavfile.read(obj.speech)
+
+ return {
+ 'value': np.cast['float'](audio)
+ }
+
+
+#----------------------------------------------------------
+
+
+class SimpleAntispoofing(View):
+ """Outputs:
+ - speech: "{{ system_user.username }}/array_1d_floats/1"
+ - file_id: "{{ system_user.username }}/text/1"
+ - client_id: "{{ system_user.username }}/text/1"
+ - attack_type: "{{ system_user.username }}/text/1"
+ - class: "{{ system_user.username }}/text/1"
+
+
+ One "file_id" is associated with a given "speech".
+ Several "speech" are associated with a given "client_id".
+ Several "client_id" are associated with a given "template_id".
+
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | speech | | speech | | speech | | speech | | speech | | speech |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ | file_id | | file_id | | file_id | | file_id | | file_id | | file_id |
+ --------------- --------------- --------------- --------------- --------------- ---------------
+ ------------------------------- ------------------------------- -------------------------------
+ | attack_type | | attack_type | | attack_type |
+ ------------------------------- ------------------------------- -------------------------------
+ --------------------------------------------------------------- -------------------------------
+ | client_id | | client_id
+ --------------------------------------------------------------- -------------------------------
+ -----------------------------------------------------------------------------------------------
+ | class |
+ -----------------------------------------------------------------------------------------------
+
+ Note: for this particular database, there is only one "client_id"
+ per "template_id".
+ """
+
+ def __init__(self):
+ super(SimpleAntispoofing, self)
+ self.output_member_map = {'class': 'cls'}
+
+
+ def index(self, root_folder, parameters):
+ Entry = namedtuple('Entry', ['cls', 'client_id', 'attack_type', 'file_id', 'speech'])
+
+ # Open the database and load the objects to provide via the outputs
+ db = bob.db.avspoof.Database()
+
+ objs_real = sorted(db.objects(protocol=parameters['protocol'],
+ groups=parameters['group'],
+ cls='real'),
+ key=lambda x: (x.client_id, x.id))
+
+ objs_attack = sorted(db.objects(protocol=parameters['protocol'],
+ groups=parameters['group'],
+ cls='attack'),
+ key=lambda x: (x.client_id, x.get_attack(), x.id))
+
+ return [ Entry('real', x.client_id, 'human', x.id, x.make_path(root_folder, '.wav')) for x in objs_real ] + \
+ [ Entry('attack', x.client_id, x.get_attack(), x.id, x.make_path(root_folder, '.wav')) for x in objs_attack ]
+
+
+ def get(self, output, index):
+ obj = self.objs[index]
+
+ if output == 'class':
+ return {
+ 'text': obj.cls
+ }
+
+ elif output == 'client_id':
+ return {
+ 'text': str(obj.client_id)
+ }
+
+ elif output == 'attack_type':
+ return {
+ 'text': obj.attack_type
+ }
+
+ elif output == 'file_id':
+ return {
+ 'text': str(obj.file_id)
+ }
+
+ elif output == 'speech':
+ rate, audio = scipy.io.wavfile.read(obj.speech)
+
+ return {
+ 'value': np.cast['float'](audio)
+ }
+
+
+#----------------------------------------------------------
+
+
+def setup_tests():
+ # Install a mock read function for the audio files
+ def mock_read(filename):
+ return 44100, np.ndarray((128,))
+
+ scipy.io.wavfile.read = mock_read
+
+
+#----------------------------------------------------------
+
+
+# Test the behavior of the views (on fake data)
+if __name__ == '__main__':
+
+ setup_tests()
+
+ view = RecognitionTraining()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol = 'smalltest',
+ group = 'train',
+ )
+ )
+ view.get('client_id', 0)
+ view.get('file_id', 0)
+ view.get('speech', 0)
+
+
+ view = RecognitionTemplates()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol = 'smalltest',
+ group = 'train',
+ purpose = 'enroll',
+ )
+ )
+ view.get('client_id', 0)
+ view.get('template_id', 0)
+ view.get('file_id', 0)
+ view.get('speech', 0)
+
+
+ view = Probes()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol = 'smalltest',
+ group = 'train',
+ )
+ )
+ view.get('template_ids', 0)
+ view.get('client_id', 0)
+ view.get('probe_id', 0)
+ view.get('file_id', 0)
+ view.get('speech', 0)
+
+
+ view = Attacks()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol = 'smalltest',
+ group = 'train',
+ )
+ )
+ view.get('template_ids', 0)
+ view.get('client_id', 0)
+ view.get('attack_id', 0)
+ view.get('file_id', 0)
+ view.get('speech', 0)
+
+
+ view = SimpleAntispoofing()
+ view.objs = view.index(
+ root_folder='',
+ parameters=dict(
+ protocol = 'smalltest',
+ group = 'train',
+ )
+ )
+ view.get('class', 0)
+ view.get('client_id', 0)
+ view.get('attack_type', 0)
+ view.get('file_id', 0)
+ view.get('speech', 0)
diff --git a/advanced/databases/avspoof/5.rst b/advanced/databases/avspoof/5.rst
new file mode 100644
index 0000000000000000000000000000000000000000..fb8a5f67432d9df6ef19ce758ad46480bc712557
--- /dev/null
+++ b/advanced/databases/avspoof/5.rst
@@ -0,0 +1 @@
+The AVspoof Database
\ No newline at end of file