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Added Add VERBO: Voice Emotion Recognition database in Portuguese Lang #19

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Jun 16, 2022
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Added Add VERBO: Voice Emotion Recognition database in Portuguese Lang #19

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3 changes: 3 additions & 0 deletions README.md
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Expand Up @@ -26,6 +26,7 @@ The table can be browsed, sorted and searched under https://superkogito.github.i
| <sub>[ANAD]</sub> | <sub>2018</sub> | <sub>1384 recording by multiple speakers.</sub> | <sub>3 emotions: angry, happy, surprised.</sub> | <sub>Audio</sub> | <sub>~2 GB</sub> | <sub>Arabic</sub> | <sub>[Arabic Natural Audio Dataset] </sub> | <sub>Open access</sub> | <sub>[CC BY-NC-SA 4.0] </sub> |
| <sub>[EmoSynth]</sub> | <sub>2018</sub> | <sub>144 audio file labelled by 40 listeners.</sub> | <sub>Emotion (no speech) defined in regard of valence and arousal.</sub> | <sub>Audio</sub> | <sub>103.4 MB</sub> | <sub>--</sub> | <sub>[The Perceived Emotion of Isolated Synthetic Audio: The EmoSynth Dataset and Results] </sub> | <sub>Open access</sub> | <sub>[CC BY 4.0] </sub> |
| <sub>[CMU-MOSEI]</sub> | <sub>2018</sub> | <sub>65 hours of annotated video from more than 1000 speakers and 250 topics.</sub> | <sub>6 Emotion (happiness, sadness, anger,fear, disgust, surprise) + Likert scale.</sub> | <sub>Audio, Video</sub> | <sub>--</sub> | <sub>English</sub> | <sub>[Multi-attention Recurrent Network for Human Communication Comprehension] </sub> | <sub>Open access</sub> | <sub>[CMU-MOSEI License] </sub> |
| <sub>[VERBO]</sub> | <sub>2018</sub> | <sub>14 different phrases by 12 speakers (6 female + 6 male) for a total of 1167 recordings. </sub> | <sub>7 emotions: Happiness, Disgust, Fear, Neutral, Anger, Surprise, Sadness </sub> | <sub>Audio</sub> | <sub>--</sub> | <sub>Portuguese</sub> | <sub>[VERBO: Voice Emotion Recognition dataBase in Portuguese Language]</sub> | <sub>Restricted access</sub> | <sub>Available for research purposes only</sub>
| <sub>[CMU-MOSI]</sub> | <sub>2017</sub> | <sub>2199 opinion utterances with annotated sentiment.</sub> | <sub>Sentiment annotated between very negative to very positive in seven Likert steps.</sub> | <sub>Audio, Video</sub> | <sub>--</sub> | <sub>English</sub> | <sub>[Multi-attention Recurrent Network for Human Communication Comprehension] </sub> | <sub>Open access</sub> | <sub>[CMU-MOSI License] </sub> |
| <sub>[MSP-IMPROV]</sub> | <sub>2017</sub> | <sub>20 sentences by 12 actors.</sub> | <sub>4 emotions: angry, sad, happy, neutral, other, without agreement</sub> | <sub>Audio, Video</sub> | <sub> -- </sub> | <sub>English</sub> | <sub>[MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception]</sub> | <sub>Restricted access</sub> | <sub>Available under an Academic License & Commercial License </sub> |
| <sub>[CREMA-D]</sub> | <sub>2017</sub> | <sub>7442 clip of 12 sentences spoken by 91 actors (48 males and 43 females).</sub> | <sub>6 emotions: angry, disgusted, fearful, happy, neutral, and sad</sub> | <sub>Audio, Video</sub> | <sub> -- </sub> | <sub>English</sub> | <sub>[CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset]</sub> | <sub>Open access</sub> | <sub>Available under the [Open Database License & Database Content License] </sub> |
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[MELD]: https://affective-meld.github.io/
[ShEMO]: https://github.com/mansourehk/ShEMO
[DEMoS]: https://zenodo.org/record/2544829
[VERBO]:https://sites.google.com/view/verbodatabase/home
[AESDD]: http://m3c.web.auth.gr/research/aesdd-speech-emotion-recognition/
[Emov-DB]: https://mega.nz/#F!KBp32apT!gLIgyWf9iQ-yqnWFUFuUHg!mYwUnI4K
[RAVDESS]: https://zenodo.org/record/1188976#.XrC7a5NKjOR
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[BEHAVIOURAL FINDINGS FROM THE TORONTO EMOTIONAL SPEECH SET]: https://www.semanticscholar.org/paper/BEHAVIOURAL-FINDINGS-FROM-THE-TORONTO-EMOTIONAL-SET-Dupuis-Pichora-Fuller/d7f746b3aee801a353b6929a65d9a34a68e71c6f/figure/2
[CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4313618/
[DEMoS: An Italian emotional speech corpus. Elicitation methods, machine learning, and perception]: https://link.springer.com/epdf/10.1007/s10579-019-09450-y?author_access_token=5pf0w_D4k9z28TM6n4PbVPe4RwlQNchNByi7wbcMAY5hiA-aXzXNbZYfsMDDq2CdHD-w5ArAxIwlsk2nC_26pSyEAcu1xlKJ1c9m3JZj2ZlFmlVoCZUTcG3Hq2_2ozMLo3Hq3Y0CHzLdTxihQwch5Q%3D%3D
[VERBO: Voice Emotion Recognition dataBase in Portuguese Language]: https://thescipub.com/pdf/jcssp.2018.1420.1430.pdf
[A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let’s Go Bus Information System]: http://www.lrec-conf.org/proceedings/lrec2012/pdf/333_Paper.pdf
[Introducing the RECOLA Multimodal Corpus of Remote Collaborative and Affective Interactions]: https://drive.google.com/file/d/0B2V_I9XKBODhNENKUnZWNFdVXzQ/view
[Multimodal Emotion Recognition]: http://personal.ee.surrey.ac.uk/Personal/P.Jackson/pub/ma10/HaqJackson_MachineAudition10_approved.pdf
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2 changes: 2 additions & 0 deletions src/index.rst
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Expand Up @@ -58,6 +58,7 @@ However, we cannot guarantee that all listed links are up-to-date. Read more in
.. _`MELD`: https://affective-meld.github.io/
.. _`ShEMO`: https://github.com/mansourehk/ShEMO
.. _`DEMoS`: https://zenodo.org/record/2544829
.. _`VERBO`: https://sites.google.com/view/verbodatabase/home
.. _`AESDD`: http://m3c.web.auth.gr/research/aesdd-speech-emotion-recognition/
.. _`Emov-DB`: https://mega.nz/#F!KBp32apT!gLIgyWf9iQ-yqnWFUFuUHg!mYwUnI4K
.. _`RAVDESS`: https://zenodo.org/record/1188976#.XrC7a5NKjOR
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.. _`EMOTIONAL SPEECH SYNTHESIS USING SUBSPACE CONSTRAINTS IN PROSODY`: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.420.8899&rep=rep1&type=pdf
.. _`Naturalistic emotional speech collectionparadigm with online game and its psychological and acoustical assessment`: https://www.jstage.jst.go.jp/article/ast/33/6/33_E1175/_pdf
.. _`EMOVO Corpus: an Italian Emotional Speech Database`: https://core.ac.uk/download/pdf/53857389.pdf
.. _`VERBO: Voice Emotion Recognition dataBase in Portuguese Language`: https://thescipub.com/pdf/jcssp.2018.1420.1430.pdf
.. _`The eNTERFACE’05 Audio-Visual Emotion Database`: http://poseidon.csd.auth.gr/papers/PUBLISHED/CONFERENCE/pdf/Martin06a.pdf
.. _`Arabic Natural Audio Dataset`: https://data.mendeley.com/datasets/xm232yxf7t/1
.. _`Introducing the Geneva Multimodal Expression Corpus for Experimental Research on Emotion Perception`: https://www.researchgate.net/publication/51796867_Introducing_the_Geneva_Multimodal_Expression_Corpus_for_Experimental_Research_on_Emotion_Perception
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1 change: 1 addition & 0 deletions src/ser-datasets.csv
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"`ANAD`_","2018","1384 recording by multiple speakers.","3 emotions: angry, happy, surprised.","Audio","2 GB","Arabic","`Arabic Natural Audio Dataset`_","Open","`CC BY-NC-SA 4.0`_"
"`EmoSynth`_","2018","144 audio file labelled by 40 listeners.","Emotion (no speech) defined in regard of valence and arousal.","Audio","0.1034 GB","--","`The Perceived Emotion of Isolated Synthetic Audio: The EmoSynth Dataset and Results`_","Open","`CC BY 4.0`_"
"`CMU-MOSEI`_","2018","65 hours of annotated video from more than 1000 speakers and 250 topics.","6 Emotion (happiness, sadness, anger,fear, disgust, surprise) + Likert scale.","Audio, Video","--","English","`Multi-attention Recurrent Network for Human Communication Comprehension`_","Open","`CMU-MOSEI License`_"
"`VERBO`_","2018","14 different phrases by 12 speakers (6 female + 6 male) for a total of 1167 recordings.","7 emotions: Happiness, Disgust, Fear, Neutral, Anger, Surprise, Sadness","Audio","--","Portuguese","`VERBO: Voice Emotion Recognition dataBase in Portuguese Language`_","Restricted","Available for research purposes only"
"`CMU-MOSI`_","2017","2199 opinion utterances with annotated sentiment.","Sentiment annotated between very negative to very positive in seven Likert steps.","Audio, Video","--","English","`Multi-attention Recurrent Network for Human Communication Comprehension`_","Open","`CMU-MOSI License`_"
"`MSP-IMPROV`_","2017","20 sentences by 12 actors.","4 emotions: angry, sad, happy, neutral, other, without agreement","Audio, Video","--","English","`MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception`_","Restricted","Academic License & Commercial License"
"`CREMA-D`_","2017","7442 clip of 12 sentences spoken by 91 actors (48 males and 43 females).","6 emotions: angry, disgusted, fearful, happy, neutral, and sad","Audio, Video","--","English","`CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset`_","Open","`Open Database License & Database Content License`_"
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