TAU Urban Acoustic Scenes 2020 Mobile, Development dataset

Audio Research Group / Tampere University

Authors

Recording and annotation

  • Henri Laakso
  • Ronal Bejarano Rodriguez
  • Toni Heittola

1. Dataset

TAU Urban Acoustic Scenes 2020 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:

  • Airport - airport
  • Indoor shopping mall - shopping_mall
  • Metro station - metro_station
  • Pedestrian street - street_pedestrian
  • Public square - public_square
  • Street with medium level of traffic - street_traffic
  • Travelling by a tram - tram
  • Travelling by a bus - bus
  • Travelling by an underground metro - metro
  • Urban park - park

Recordings were made with three devices (A, B and C) that captured audio simultaneously and 6 simulated devices (S1-S6). Each acoustic scene has 1440 segments (240 minutes of audio) recorded with device A (main device) and 108 segments of parallel audio (18 minutes) each recorded with devices B,C, and S1-S6. The dataset contains in total 64 hours of audio.

The dataset was collected by Tampere University of Technology between 05/2018 - 11/2018. The data collection has received funding from the European Research Council under the ERC Grant Agreement 637422 EVERYSOUND.

ERC

Preparation of the dataset

The dataset was recorded in 12 large European cities: Amsterdam, Barcelona, Helsinki, Lisbon, London, Lyon, Madrid, Milan, Prague, Paris, Stockholm, and Vienna. For all acoustic scenes, audio was captured in multiple locations: different streets, different parks, different shopping malls. In each location, multiple 2-3 minute long audio recordings were captured in a few slightly different positions (2-4) within the selected location. Collected audio material was cut into segments of 10 seconds length.

The main recording device (referred to as device A) consists of a binaural Soundman OKM II Klassik/studio A3 electret in-ear microphone and a Zoom F8 audio recorder using 48 kHz sampling rate and 24 bit resolution. During the recording, the microphones were worn by the recording person in the ears, and head movement was kept to minimum.

Devices B and C are commonly available customer devices (e.g. smartphones, cameras) and were handled in typical ways (e.g. hand held). The audio recordings from these devices are of different quality than device A. All simultaneous recordings are time synchronized.

Post-processing of the recorded audio involves aspects related to privacy of recorded individuals, and possible errors in the recording process. The material was screened for content, and segments containing close microphone conversation were eliminated. Some interferences from mobile phones are audible, but are considered part of real-world recording process. In addition, data from device A was resampled and averaged into a single channel, to align with the properties of the data recorded with devices B and C.

Additionally, 11 mobile devices S1-S11 are simulated using the audio recorded with device A, impulse responses recorded with real devices, and additional dynamic range compression, in order to simulate realistic recordings. A recording from device A is processed through convolution with the selected Si impulse response, then processed with a selected set of parameters for dynamic range compression (device specific). The impulse responses are proprietary data and will not be published.

All provided audio data is single-channel, having a 44.1 KHz sampling rate, and 24 bit resolution.

A subset of the dataset has been previously published as TUT Urban Acoustic Scenes 2019 Development dataset. Audio segment filenames are retained for the segments coming from this dataset.

Dataset statistics

The development set contains data from 10 cities and 9 devices: 3 real devices (A, B, C) and 6 simulated devices (S1-S6). Data from devices B, C and S1-S6 consists of randomly selected segments from the simultaneous recordings, therefore all overlap with the data from device A, but not necessarily with each other. The total amount of audio in the development set is 64 hours. The evaluation dataset (TAU Urban Acoustic Scenes 2020 Mobile evaluation) contains data from all 12 cities, and five new devices (not available in the development set): real device D and simulated devices S7-S11.

Device A

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 1440 128 149 144  145 144 144 156 144 158 128
Bus 1440 144 144 144  144 144 144 144 144 144 144
Metro 1440 141 144 144  146 144 144 144 144 145 144
Metro station 1440 144 144 144  144 144 144 144 144 144 144
Park 1440 144 144 144  144 144 144 144 144 144 144
Public square 1440 144 144 144  144 144 144 144 144 144 144
Shopping mall 1440 144 144 144  144 144 144 144 144 144 144
Street, pedestrian 1440 145 145 144  145 144 144 144 144 145 140
Street, traffic 1440 144 144 144  144 144 144 144 144 144 144
Tram 1440 143 145 144  144 144 144 144 144 144 144
Total 14400 1421 1447 1440 1444 1440 1440 1452 1440 1456  1420
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 40 4 3 4 3 4 4 4 6 5  3
Bus 71 4 4 11 7 7 7 11 10 6  4
Metro 67 3 5 11 4 9 8 9 10 4  4
Metro station 57 5 6 4 12 5 4 9 4 4  4
Park 41 4 4 4 4 4 4 4 4 5  4
Public_square 43 4 4 4 4 5 4 4 6 4  4
Shopping mall 36 4 4 4 2 3 3 4 4 4  4
Street, pedestrian 46 7 4 4 4 4 5 5 5 4  4
Street, traffic 43 4 4 4 5 4 6 4 4 4  4
Tram 70 4 4 6 9 7 11 9 11 5  4
Total 514 43 42 56 54 52 56 63 65 45  39

Device B

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 36 3 3 4 3 3 4 4 5 4  3
Bus 57 4 4 9 7 6 5 8 7 3  4
Metro 47 3 4 6 4 6 5 6 6 4  4
Metro station 45 4 4 3 8 5 3 7 3 4  4
Park 37 4 4 4 4 4 3 4 3 3  4
Public_square 38 4 4 4 4 5 3 4 4 3  3
Shopping mall 34 4 4 4 2 3 3 4 4 3  3
Street, pedestrian 43 6 3 4 4 4 5 5 4 4  4
Street, traffic 41 4 4 4 4 4 6 4 4 4  4
Tram 50 4 4 5 6 5 5 7 7 3  4
Total 428 40 37 47 46 44 42 53 47 35  37

Device C

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 38 4 3 4 3 3 4 4 5 5  3
Bus 50 4 4 7 6 5 4 7 7 3  3
Metro 54 3 3 6 4 9 6 7 8 4  4
Metro station 48 5 3 4 8 5 4 7 4 4  4
Park 39 4 4 4 4 4 4 4 4 3  4
Public_square 40 4 3 4 4 4 4 4 6 3  4
Shopping mall 35 4 4 4 2 3 3 4 4 3  4
Street, pedestrian 41 6 3 4 4 3 5 4 5 4  3
Street, traffic 40 4 3 4 4 4 6 4 4 4  3
Tram 51 4 4 5 6 4 8 6 7 3  4
Total 426 42 34 46 45 44 48 51 54 36  36

Device S1

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 37 4 3 4 3 4 4 4 4 4  3
Bus 54 4 4 8 6 6 6 7 6 3  4
Metro 50 3 3 8 4 7 6 6 6 4  3
Metro station 48 5 4 4 9 5 4 5 4 4  4
Park 36 4 4 4 4 3 4 3 3 3  4
Public_square 37 4 4 4 4 4 4 3 3 3  4
Shopping mall 33 4 4 4 2 3 3 3 3 3  4
Street, pedestrian 40 6 3 4 4 3 5 2 5 4  4
Street, traffic 40 4 4 4 4 4 6 3 3 4  4
Tram 52 4 4 5 7 6 7 6 6 3  4
Total 427 42 37 49 47 45 49 42 43 35  38

Device S2

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 36 3 3 4 3 4 4 4 4 4  3
Bus 58 4 4 9 6 6 7 9 6 3  4
Metro 55 3 3 10 4 8 8 5 7 4  3
Metro station 49 5 4 4 7 5 4 8 4 4  4
Park 38 4 4 4 4 4 4 4 4 2  4
Public_square 41 4 4 4 4 5 4 4 5 3  4
Shopping mall 34 4 4 3 2 3 3 4 4 3  4
Street, pedestrian 42 7 3 4 4 3 5 5 4 4  3
Street, traffic 42 4 4 4 5 4 6 4 4 4  3
Tram 51 4 4 5 7 6 7 7 4 3  4
Total 446 42 37 51 46 48 52 54 46 34  36

Device S3

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 36 3 3 4 3 4 4 4 4 4  3
Bus 50 4 4 6 5 6 6 7 5 3  4
Metro 50 3 3 10 4 5 6 4 8 3  4
Metro station 44 4 4 4 6 5 4 7 3 4  3
Park 39 4 4 4 4 4 4 4 4 3  4
Public_square 39 4 4 3 4 5 4 4 4 3  4
Shopping mall 32 4 4 3 2 3 3 4 3 3  3
Street, pedestrian 39 6 3 3 4 4 4 5 3 4  3
Street, traffic 40 4 4 4 5 4 5 4 3 3  4
Tram 50 4 4 5 8 5 7 6 5 3  3
Total 419 40 37 46 45 45 47 49 42 33  35

Device S4

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 36 3 3 4 3 4 4 4 4 4  3
Bus 53 4 4 9 5 6 5 6 7 3  4
Metro 50 3 2 8 4 7 6 7 6 4  3
Metro station 47 5 4 4 7 5 4 6 4 4  4
Park 38 4 3 4 4 4 4 4 4 3  4
Public_square 38 4 4 3 3 5 4 4 4 3  4
Shopping mall 35 4 4 4 2 3 3 4 4 3  4
Street, pedestrian 42 7 3 3 4 4 4 4 5 4 4
Street, traffic 41 4 4 4 4 4 5 4 4 4  4
Tram 51 4 4 6 6 7 5 7 5 3  4
Total 431 42 35 49 42 49 44 50 47 35  38

Device S5

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 38 4 3 4 3 4 4 3 5 5  3
Bus 54 3 4 6 6 6 7 8 7 3  4
Metro 51 3 3 7 4 8 6 6 7 4  3
Metro station 45 5 3 3 7 4 4 7 4 4  4
Park 36 3 4 3 3 4 4 4 4 3  4
Public_square 39 3 4 3 4 4 4 4 6 3  4
Shopping mall 33 3 4 3 2 3 3 4 4 3  4
Street, pedestrian 42 6 3 4 4 4 4 5 5 4 3
Street, traffic 38 3 3 4 4 4 4 4 4 4  4
Tram 50 4 4 4 6 5 8 7 6 3  3
Total 426 37 35 41 43 46 48 52 52 36  36

Device S6

Audio segments
Scene class Segments Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 108 12 12 12  11 11 10 10 10 10 10
Bus 108 12 12 12  11 11 10 10 10 10 10
Metro 108 12 12 12  11 11 10 10 10 10 10
Metro station 108 12 12 12  11 11 10 10 10 10 10
Park 108 12 12 12  11 11 10 10 10 10 10
Public square 108 12 12 12  11 11 10 10 10 10 10
Shopping mall 108 12 12 12  11 11 10 10 10 10 10
Street, pedestrian 108 12 12 12  11 11 10 10 10 10 10
Street, traffic 108 12 12 12  11 11 10 10 10 10 10
Tram 108 12 12 12  11 11 10 10 10 10 10
Total 1080 120 120 120 110 110 100 100 100 100  100
Recording locations
Scene class Locations Barcelona Helsinki Lisbon London Lyon Milan  Paris Prague Stockholm Vienna
Airport 36 4 3 4 3 4 3 3 5 4  3
Bus 55 3 4 9 7 6 5 9 6 2  4
Metro 51 3 2 7 4 7 6 7 8 3  4
Metro station 47 5 4 4 9 3 3 7 4 4  4
Park 37 3 4 4 4 4 3 4 4 3  4
Public_square 39 4 4 4 4 4 3 4 5 3  4
Shopping mall 33 3 4 4 2 3 2 4 4 3  4
Street, pedestrian 39 5 3 4 4 3 4 4 4 4 4
Street, traffic 39 3 4 3 4 4 5 4 4 4  4
Tram 56 4 4 6 7 6 7 6 9 3  4
Total 432 37 35 49 48 44 41 52 53 33  39

File structure

dataset root
│   README.md               this file, markdown-format
│   README.html             this file, html-format
│   meta.csv                meta data, csv-format with a header row, [audio file (string)][tab][scene label (string)][tab][identifier (string)][tab][source_label (string)]
│
└───audio                   23040 audio segments, 24-bit 44.1kHz mono
│   │   airport-barcelona-0-0-a.wav     file naming convention: [scene label]-[city]-[location id]-[segment id]-[device id].wav
│   │   airport-barcelona-0-1-a.wav
│   │   airport-barcelona-0-3-a.wav
│   │   ...
│   │   airport-barcelona-1-17-a.wav
│   │   airport-barcelona-1-17-b.wav
│   │   airport-barcelona-1-17-c.wav
│   │   ...
│
└───evaluation_setup        cross-validation setup, 1 fold
    │   fold1_train.csv     training file list, csv-format with a header row, [audio file (string)][tab][scene label (string)]
    │   fold1_test.csv      testing file list, csv-format with a header row, [audio file (string)]
    │   fold1_evaluate.csv  evaluation file list, fold1_test.txt with added ground truth, csv-format with a header row, [audio file (string)][tab][scene label (string)]

2. Usage

The partitioning of the data was done based on the location of the original recordings. All segments recorded at the same location were included into a single subset - either development dataset or evaluation dataset. For each acoustic scene, 1440 segments recorded with device A, 108 segments recorded with device B, C and S1-S6 were included in the development dataset provided here. Evaluation dataset is provided separately.

Training / test setup

A suggested training/test partitioning of the development set is provided in order to make results reported with this dataset uniform. The partitioning is done such that the segments recorded at the same location are included into the same subset - either training or testing. The partitioning is done aiming for a 70/30 ratio between the number of segments in training and test subsets while taking into account recording locations, and selecting the closest available option.

Data from devices A, B, C, S1, S2, S3 are available in both training and test sets. Audio segments coming from devices S4, S5, and S6 are used only for testing. Since the dataset includes balanced amount of material from devices (B, C, and S1-S6), this partitioning will leave a small subset of data from devices S4-S6 unused in the training / test setup. This material can be used when using full dataset to train the system and testing it with evaluation dataset.

The setup is provided with the dataset in the directory evaluation_setup.

Statistics

Scene class Train / Segments Train / Locations Test / Segments Test / Locations Unused / Segments Unused / Locations
Airport 1394 28 297 12 613 40
Bus 1400 51 297 19 607 66
Metro 1382 47 297 20 625 65
Metro station 1380 40 297 16 627 55
Park 1429 30 297 11 578 39
Public square 1428 31 297 12 579 42
Shopping mall 1374 26 297 10 633 35
Street, pedestrian 1386 32 297 14 621 45
Street, traffic 1413 31 297 12 594 43
Tram 1379 49 297 20 628 67
Total 13965 365 2970 146 6105 497

Statistics; number of segments in train / test setup

Scene class Train / Device A Train / Device B,C,S1-S3 Test / Device A Test / Device Device B,C,S1-S3 Test / Device S4-S6
Airport 1019 75 33 33 33
Bus 1025 75 33 33 33
Metro 1007 75 33 33 33
Metro station 1005 75 33 33 33
Park 1054 75 33 33 33
Public square 1053 75 33 33 33
Shopping mall 999 75 33 33 33
Street, pedestrian 1011 75 33 33 33
Street, traffic 1038 75 33 33 33
Tram 1004 75 33 33 33
Total 10215 750 330 5 x 330 = 1650 3 x 330 = 990

Training

evaluation setup\fold1_train.csv
training file list (in csv-format with a header row)

Format:

[audio file (string)][tab][scene label (string)]

Testing

evaluation setup\fold1_test.csv
testing file list (in csv-format with a header row)

Format: [audio file (string)]

Evaluating

evaluation setup\fold1_evaluate.csv
evaluation file list (in csv-format with a header row), same as fold1_test.csv but with additional reference information. These two files are provided separately to prevent contamination with ground truth when testing the system

Format: 

[audio file (string)][tab][scene label (string)]

Custom setups

If not using the provided training/test setup, pay attention to the segments recorded at the same location. Location identifier can be found from meta.csv or from audio file names:

[scene label]-[city]-[location id]-[segment id]-[device id].wav

Make sure that all files having same location id are placed on the same side of the evaluation. Device id can be a, b, or c.

3. Changelog

v1.0 / 2020-02-18

  • Initial commit

4. License

License permits free academic usage. Any commercial use is strictly prohibited. For commercial use, contact dataset authors.

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