TAU Urban Acoustic Scenes 2020 Mobile, Development dataset

Audio Research Group / Tampere University

Authors

Toni Heittola (toni.heittola@tuni.fi, http://www.cs.tut.fi/~heittolt/)
Annamaria Mesaros (annamaria.mesaros@tuni.fi, http://www.cs.tut.fi/~mesaros/)
Tuomas Virtanen (tuomas.virtanen@tuni.fi, http://www.cs.tut.fi/~tuomasv/)

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.

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	107	11	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	107	11	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	1078	118	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	37	3	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	427	39	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	107	11	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	107	12	12	12	10	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	107	11	12	12	11	11	10	10	10	10	10
Total	1077	118	120	120	109	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	436	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                   23035 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	1393	28	296	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	1427	31	297	12	579	42
Shopping mall	1373	26	297	10	633	35
Street, pedestrian	1386	32	297	14	621	45
Street, traffic	1413	31	297	12	594	43
Tram	1379	49	296	20	628	67
Total	13962	365	2968	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

v2.0 / 2020-05-11

Fixed synchronization between some segments from devices A, B, C. In this process, 118 files got replaced with correct audio content, and 5 files were removed due to unavailability of correct parallel recording from specific device.
- Files replaced (118): airport-barcelona-0-2-c, airport-barcelona-1-25-c, airport-barcelona-1-33-c, airport-barcelona-1-41-b, airport-barcelona-1-47-b, airport-barcelona-1-61-b, airport-barcelona-1-67-b, airport-barcelona-1-71-b, airport-barcelona-1-72-b, airport-barcelona-1-76-c, airport-barcelona-1-81-c, airport-barcelona-1-91-b, airport-barcelona-2-102-c, airport-barcelona-2-109-b, airport-barcelona-2-109-c, airport-barcelona-203-6122-b, airport-barcelona-203-6130-b, airport-barcelona-203-6131-b, airport-barcelona-203-6131-c, airport-barcelona-203-6132-b, airport-barcelona-203-6134-c, airport-barcelona-203-6135-c, airport-barcelona-203-6137-c, airport-helsinki-204-6141-b, airport-helsinki-204-6143-c, airport-helsinki-204-6148-b, airport-helsinki-204-6149-c, airport-helsinki-204-6155-c, airport-helsinki-204-6159-b, airport-helsinki-204-6160-b, airport-helsinki-204-6163-c, airport-helsinki-3-114-c, airport-helsinki-3-138-c, airport-helsinki-3-147-b, airport-helsinki-3-149-c, airport-helsinki-3-154-c, airport-helsinki-3-164-b, airport-helsinki-3-167-b, airport-helsinki-3-168-b, airport-helsinki-4-170-c, airport-helsinki-4-178-c, airport-helsinki-4-183-b, airport-helsinki-4-188-c, airport-helsinki-4-196-b, airport-helsinki-4-206-c, airport-helsinki-4-219-b, airport-helsinki-4-220-b, airport-vienna-13-516-c, airport-vienna-13-520-c, airport-vienna-13-522-c, airport-vienna-13-526-b, airport-vienna-13-545-b, airport-vienna-13-545-c, airport-vienna-13-547-b, airport-vienna-13-549-b, airport-vienna-13-549-c, airport-vienna-13-552-b, airport-vienna-209-6373-c, airport-vienna-209-6375-b, airport-vienna-209-6381-b, airport-vienna-209-6381-c, airport-vienna-209-6384-c, airport-vienna-209-6386-b, bus-helsinki-20-789-c, metro-barcelona-220-6644-c, metro-barcelona-220-6663-b, metro-barcelona-220-6676-c, metro-barcelona-220-6681-b, metro-barcelona-41-1232-b, metro-barcelona-41-1238-b, metro-barcelona-42-1269-c, metro-barcelona-42-1273-c, metro-barcelona-42-1277-b, metro-barcelona-42-1277-c, metro-barcelona-42-1281-c, metro-barcelona-42-1291-c, metro-barcelona-42-1296-b, metro_station-barcelona-63-1889-c, public_square-barcelona-108-3091-c, public_square-barcelona-108-3096-c, public_square-barcelona-108-3105-c, public_square-barcelona-108-3109-b, shopping_mall-london-131-3915-b, shopping_mall-london-131-3926-b, shopping_mall-london-131-3926-c, shopping_mall-london-131-3927-c, shopping_mall-london-131-3929-b, shopping_mall-london-131-3933-b, shopping_mall-london-131-3943-b, shopping_mall-london-131-3943-c, shopping_mall-london-131-3944-c, shopping_mall-london-256-7741-b, shopping_mall-london-256-7754-c, shopping_mall-london-256-7759-c, street_pedestrian-vienna-160-4866-b, street_pedestrian-vienna-160-4872-b, street_pedestrian-vienna-160-4880-b, street_pedestrian-vienna-160-4889-b, street_pedestrian-vienna-160-4896-b, street_traffic-lisbon-1171-45702-b, street_traffic-lyon-1220-44647-b, street_traffic-lyon-1220-44730-c, street_traffic-lyon-1220-44830-c, street_traffic-lyon-1220-44939-c, tram-barcelona-179-5519-c, tram-barcelona-179-5525-c, tram-barcelona-179-5556-b, tram-barcelona-179-5556-c, tram-barcelona-180-5559-c, tram-barcelona-180-5567-b, tram-barcelona-180-5571-b, tram-barcelona-180-5595-b, tram-barcelona-275-8385-c, tram-barcelona-275-8394-b, tram-barcelona-275-8396-c, tram-barcelona-275-8398-b, tram-barcelona-275-8398-c, tram-barcelona-275-8400-b
- Files removed (5): airport-barcelona-1-87-c, airport-barcelona-203-6132-b, shopping_mall-london-131-3930-c, public_square-barcelona-108-3109-b, tram-barcelona-275-8394-c

4. License

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

Copyright (c) 2020 Tampere University and its licensors
All rights reserved.
Permission is hereby granted, without written agreement and without license or royalty
fees, to use and copy the TAU Urban Acoustic Scenes 2020 Mobile (“Work”) described in this document
and composed of audio and metadata. This grant is only for experimental and non-commercial
purposes, provided that the copyright notice in its entirety appear in all copies of this Work,
and the original source of this Work, (Audio Research Group at Tampere University of Technology),
is acknowledged in any publication that reports research using this Work.
Any commercial use of the Work or any part thereof is strictly prohibited.
Commercial use include, but is not limited to:
- selling or reproducing the Work
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OF THIS WORK AND ITS DOCUMENTATION, EVEN IF TAMPERE UNIVERSITY OR ITS
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