Primus_CP-JKU_task2_2.meta.yaml 5.58 KB
Newer Older
Paul Primus's avatar
add  
Paul Primus committed
1
2
3
4
5
6
7
# Submission information
submission:

  # Submission label
  # Label is used to index submissions.
  # Generate your label following way to avoid overlapping codes among submissions:
  # [Last name of corresponding author]_[Abbreviation of institute of the corresponding author]_task[task number]_[index number of your submission (1-4)]
Paul Primus's avatar
Paul Primus committed
8
  label: Primus_CP-JKU_task2_2
Paul Primus's avatar
add  
Paul Primus committed
9
10
11

  # Submission name
  # This name will be used in the results tables when space permits.
12
  name: Best Outlier Exposed ResNet per Machine Type
Paul Primus's avatar
add  
Paul Primus committed
13
14
15
16

  # Submission name abbreviated
  # This abbreviated name will be used in the results table when space is tight.
  # Use a maximum of 10 characters.
Paul Primus's avatar
Paul Primus committed
17
  abbreviation: OER
Paul Primus's avatar
add  
Paul Primus committed
18

Paul Primus's avatar
Paul Primus committed
19
  # Authors of the submitted system.
Paul Primus's avatar
add  
Paul Primus committed
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
  # Mark authors in the order you want them to appear in submission lists.
  # One of the authors has to be marked as corresponding author, this will be listed next to the submission in the results tables.
  authors:

    # First author
    - lastname: Primus
      firstname: Paul
      email: paul.primus@jku.at                # Contact email address
      corresponding: true                         # Mark true for one of the authors

      # Affiliation information for the author
      affiliation:
        institution: JKU
        department: Computational Perception
        location: Austria, Linz
# System information
system:

  # System description, metadata provided here will be used to do a meta-analysis of the submitted system.
  # Use general level tags, when possible use the tags provided in comments.
  # If information field is not applicable to the system, use "!!null".
  description:

    # Audio input
    # Please specify all sampling rates (comma-separated list).
    # e.g. 16kHz, 22.05kHz, 44.1kHz
    input_sampling_rate: 16kHz

    # Data augmentation methods
    # Please specify all methods used (comma-separated list).
    # e.g. mixup, time stretching, block mixing, pitch shifting, ...
    data_augmentation: !!null

    # Front-end (preprocessing) methods
    # Please specify all methods used (comma-separated list).
    # e.g. HPSS, WPE, NMF, NN filter, RPCA, ...
    front_end: !!null

    # Acoustic representation
    # one or multiple labels, e.g. MFCC, log-mel energies, spectrogram, CQT, raw waveform, ...
    acoustic_features: log-mel energies

    # Embeddings
    # Please specify all embedings used (comma-separated list).
    # one or multiple, e.g. VGGish, OpenL3, ...
    embeddings: !!null
Paul Primus's avatar
Paul Primus committed
66

Paul Primus's avatar
add  
Paul Primus committed
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
    # Machine learning
    # In case using ensemble methods, please specify all methods used (comma-separated list).
    # e.g. AE, VAE, GAN, GMM, k-means, OCSVM, normalizing flow, CNN, LSTM, random forest, ensemble, ...
    machine_learning_method: CNN

    # Method for aggregating predictions over time
    # Please specify all methods used (comma-separated list).
    # e.g. average, median, maximum, minimum, ...
    aggregation_method: average

    # Ensemble method subsystem count
    # In case ensemble method is not used, mark !!null.
    # e.g. 2, 3, 4, 5, ...
    ensemble_method_subsystem_count: !!null

    # Decision making in ensemble
    # e.g. average, median, maximum, minimum, ...
    decision_making: !!null

    # External data usage method
    # Please specify all usages (comma-separated list).
    # e.g. simulation of anomalous samples, embeddings, pre-trained model, ...
    external_data_usage: !!null

    # Usage of the development dataset
    # Please specify all usages (comma-separated list).
    # e.g. development, pre-training, fine-tuning
    development_data_usage: development

  # System complexity, metadata provided here may be used to evaluate submitted systems from the computational load perspective.
  complexity:

    # Total amount of parameters used in the acoustic model.
    # For neural networks, this information is usually given before training process in the network summary.
    # For other than neural networks, if parameter count information is not directly available, try estimating the count as accurately as possible.
    # In case of ensemble approaches, add up parameters for all subsystems.
    # In case embeddings are used, add up parameter count of the embedding extraction networks and classification network.
    # Use numerical value.
Paul Primus's avatar
Paul Primus committed
105
    total_parameters: 12000000
Paul Primus's avatar
add  
Paul Primus committed
106
107
108
109

  # List of external datasets used in the submission.
  # Development dataset is used here only as an example, list only external datasets
  external_datasets:
Paul Primus's avatar
Paul Primus committed
110

Paul Primus's avatar
add  
Paul Primus committed
111
112
113
114
115
116
117
118
    # Dataset name
    - name: DCASE 2020 Challenge Task 2 Development Dataset

      # Dataset access URL
      url: https://zenodo.org/record/3678171

  # URL to the source code of the system [optional, highly recommended]
  # Reproducibility will be used to evaluate submitted systems.
119
  source_code: https://gitlab.cp.jku.at/paulp/dcase2020_task2
Paul Primus's avatar
add  
Paul Primus committed
120
121
122
123
124
125
126
127
128
129
130

# System results
results:
  development_dataset:

    # System results for development dataset.
    # Full results are not mandatory, however, they are highly recommended as they are needed for a thorough analysis of the challenge submissions.
    # If you are unable to provide all results, also incomplete results can be reported.

    # Average of AUCs over all Machine IDs [%]
    # No need to round numbers
Paul Primus's avatar
Paul Primus committed
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
	fan:
	  averaged_auc: 0.9286317167841518
	  averaged_pauc: 0.8352913487070679
	pump:
	  averaged_auc: 0.9297781495399142
	  averaged_pauc: 0.8722867745313565
	slider:
	  averaged_auc: 0.9894779962546816
	  averaged_pauc: 0.9454464813719693
	ToyCar:
	  averaged_auc: 0.9566950093931226
	  averaged_pauc: 0.8961968600747151
	ToyConveyor:
	  averaged_auc: 0.8526503235962499
	  averaged_pauc: 0.7259891865658302
	valve:
	  averaged_auc: 0.9776656162464985
	  averaged_pauc: 0.9357400855078873