emozionalmente

Created by Fabio Catania

version	1.0.0
license	CC-BY-4.0
usage	commercial
languages	ita
format	wav
channel	1
sampling rate	16000, 44100
bit depth	16
duration	0 days 06:18:17.953674178
files	6902, duration distribution: 0.8 s 13.9 s
repository	audb-public

Description

Emozionalmente is an extensive, crowdsourced Italian emotional speech corpus. The dataset consists of 6902 labeled samples acted out by 431 amateur actors while verbalizing 18 different sentences expressing the Big Six emotions (anger, disgust, fear, joy, sadness, surprise) plus neutrality. Labels represent the emotional communicative intention of the actors (i.e., the seven emotional states). Recordings were generally obtained with non-professional equipment. They are .wav files, mono-channel, and have a sample size of 16 bits and a sample rate of 16000 Hz. Each audio recording lasts 3.81 seconds (SD = 0.99 seconds). The emotional content of the clips were validated by asking 829 humans (5 evaluations per audio) to guess the emotion contained in each recording. Humans obtained a general accuracy of 66%.

Example

audio/1616256756877.wav

Tables

Click on a row to toggle a preview.

ID	Type	Columns
emotion.categories.dev.desired	filewise	emotion	file emotion audio/1614951631538.wav anger audio/1613994293936.wav anger audio/1613562322650.wav anger audio/1614266094803.wav anger audio/1615229375102.wav anger 1686 rows x 1 column
emotion.categories.dev.gold_standard	filewise	emotion, emotion.agreement	file emotion emotion.agreement audio/1614951631538.wav no_agreement 0.4 audio/1613994293936.wav anger 1.0 audio/1613562322650.wav anger 1.0 audio/1614266094803.wav no_agreement 0.4 audio/1615229375102.wav surprise 0.6 1686 rows x 2 columns
emotion.categories.dev.votes	filewise	anger, disgust, fear, happiness, neutral, sadness, surprise	file anger disgust fear happiness neutral sadness surprise audio/1614951631538.wav 2 2 0 0 0 0 1 audio/1613994293936.wav 5 0 0 0 0 0 0 audio/1613562322650.wav 5 0 0 0 0 0 0 audio/1614266094803.wav 2 0 0 1 0 0 2 audio/1615229375102.wav 2 0 0 0 0 0 3 1686 rows x 7 columns
emotion.categories.test.desired	filewise	emotion	file emotion audio/1617135480050.wav anger audio/1613586149044.wav anger audio/1617135448748.wav anger audio/1616505237674.wav anger audio/1614359087222.wav anger 1228 rows x 1 column
emotion.categories.test.gold_standard	filewise	emotion, emotion.agreement	file emotion emotion.agreement audio/1617135480050.wav anger 0.4 audio/1613586149044.wav anger 0.8 audio/1617135448748.wav anger 1.0 audio/1616505237674.wav anger 0.6 audio/1614359087222.wav surprise 0.6 1228 rows x 2 columns
emotion.categories.test.votes	filewise	anger, disgust, fear, happiness, neutral, sadness, surprise	file anger disgust fear happiness neutral sadness surprise audio/1617135480050.wav 2 0 0 1 1 0 1 audio/1613586149044.wav 4 0 0 0 1 0 0 audio/1617135448748.wav 5 0 0 0 0 0 0 audio/1616505237674.wav 3 0 0 0 0 0 2 audio/1614359087222.wav 2 0 0 0 0 0 3 1228 rows x 7 columns
emotion.categories.train.desired	filewise	emotion	file emotion audio/1613671614352.wav anger audio/1613658275427.wav anger audio/1613324357435.wav anger audio/1614274086698.wav anger audio/1612982146424.wav anger 3988 rows x 1 column
emotion.categories.train.gold_standard	filewise	emotion, emotion.agreement	file emotion emotion.agreement audio/1613671614352.wav neutral 0.4 audio/1613658275427.wav anger 0.8 audio/1613324357435.wav anger 0.8 audio/1614274086698.wav anger 0.6 audio/1612982146424.wav anger 0.6 3988 rows x 2 columns
emotion.categories.train.votes	filewise	anger, disgust, fear, happiness, neutral, sadness, surprise	file anger disgust fear happiness neutral sadness surprise audio/1613671614352.wav 1 0 0 0 2 1 1 audio/1613658275427.wav 4 0 0 1 0 0 0 audio/1613324357435.wav 4 0 0 0 1 0 0 audio/1614274086698.wav 3 1 0 0 0 0 1 audio/1612982146424.wav 3 0 0 0 2 0 0 3988 rows x 7 columns
files	filewise	speaker, transcription	file speaker transcription audio/1614951631538.wav d4bbc5043503b9aed309ede00854ee48937684b57a1cc030ee5f42986fbfed7c s0 audio/1613671614352.wav b830cbf6e79aeeeec1fbf2ef3be741628ffc574c9b15f30634b8e8cc56bd17b9 s1 audio/1613994293936.wav acdd987f9c1700b25898d3bd30c201df5ad4f34b3ca5ebeb7a8f02d240eeb864 s2 audio/1617135480050.wav 28043d2516f2d956b81ce66cc01fbd427ac54ff1eb3a07dae906e9be50a92024 s0 audio/1613658275427.wav 5b8476bb94a4a1a17df32b417ec035029f48e4487c9055203fb02353eccd46a1 s3 6902 rows x 2 columns
speaker	misc	age, gender, mother_tongue	speaker age gender mother_tongue f04bb0e6361c05acba4d5185a2d372177bdb77898c1a213f5dfe5c1d60331ea1 30 female italian b395b3d82da20e930e20220a5ab4de9adb9a12aaa7cecf17fc09d3a95b3edcb6 26 male italian 69a6f8fa8a7d2e7338bddab3f872ba3532c914f62ebfebe9e11b88be24209fee 26 female italian 5b1d678a1b4936c172e8c239785f89a2693f7603890c413fffc9e8629243cd77 54 female italian 1718aa7e2d0821e3ade5783b4e045ab5930ec22054a0fe5e80146dfce17fae3d 11 female italian 431 rows x 3 columns

Schemes

ID	Dtype	Min	Max	Labels	Mappings
age	int	0
emotion	str			anger, disgust, fear, happiness, neutral, no_agreement, sadness, surprise	original
emotion.agreement	float	0	1
gender	str			female, male, other
mother_tongue	str			italian
speaker	str			00a0efc0faaeb5a288481a25b5d0b7d4c0b070120c6d61be6ef7b255fcdfd17f, 00cb13bcf2382ca6eea64f955fc100530bb625a8e646ca83a2c207fd1d460dcd, 01de3a316dafa26a6e15d40720bc94e0706da6e0831274ea04dc25bccf87de9b, 026c4643a1d88e86eb050ba36c1b9de370ec06a34d58152fba030b80c1f7f573, 032bd54539dc739de8c4d77eda2bee1f933a6dd243e4447977b6b39b4d4f83bb, 03f34507d21d41467491672837afd7a5bcfb46357a300202d48c6437f359d5c8, 0518bb1812bd73aeb1a16e59f6205fca9f97ad2975fbe1a5ce10ef9389de091e, […], fdc94cca304ff508ca4791c1c56f307e4a9d2b5377e9cf1174a4182d7e664385, fe5a73de495ae5b09dcc4b895077ddc389ca689a95096dfcfe5814e7256fe794, fe9d679c7c9b995f2e68dae1261d951212cf92bde2ed7db234633f73dc447b30, fed370a920999e1f0e9ec1aa991e6d2be1b5c96f4268b9995329ee996de953f6, ff169b904af82953988d069875f82df46ae385e13949de9f8dba7503a76a3eca, ff1d25f750dcd0053c95aa615cafabb23e8dcf92e119155c1be68ac54a38f358, ff52b456027ce6b6692e375839d865ca9c1b2b73bbe096317f029e8872f36ab2, ffceba26ef879ad0650c42becbe7f1a7ff301cc763a92611d71a56dfb386aca4	age, gender, mother_tongue
transcription	str			s0, s1, s10, s11, s12, s13, s14, […], s2, s3, s4, s5, s6, s7, s8, s9	✓
votes	int	0