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From: SuperKogito <SuperKogito@users.noreply.github.com>
Date: Sun, 23 Jun 2024 16:34:01 +0000
Subject: [PATCH] deploy: 721f058965122ce58f947d3ab0b27ebee3329ccd

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 <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this headline">#</a></h1>
 <p>Spoken Emotion Recognition Datasets: A collection of datasets for the purpose of emotion recognition/detection in speech.
 The table is chronologically ordered and includes a description of the content of each dataset along with the emotions included.</p>
-<table class="datatable table" id="id23">
-<caption><span class="caption-text">SER-Datasets</span><a class="headerlink" href="#id23" title="Permalink to this table">#</a></caption>
+<table class="datatable table" id="id29">
+<caption><span class="caption-text">SER-Datasets</span><a class="headerlink" href="#id29" title="Permalink to this table">#</a></caption>
 <colgroup>
 <col style="width: 10%" />
 <col style="width: 10%" />
@@ -223,6 +223,50 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 </tr>
 </thead>
 <tbody>
+<tr class="row-even"><td><p><a class="reference external" href="https://github.com/amu-cai/nEMO">nEmo</a></p></td>
+<td><p>2024</p></td>
+<td><p>3 hours of samples recorded with the participation of nine actors.</p></td>
+<td><p>6 emotions: anger, fear, happiness, sadness, surprised, and neutral.</p></td>
+<td><p>Audio</p></td>
+<td><p>0.434 GB</p></td>
+<td><p>Polish</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2404.06292">nEMO: Dataset of Emotional Speech in Polish</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/records/10694370">EMOVOME</a></p></td>
+<td><p>2024</p></td>
+<td><p>999 spontaneous voice messages from 100 Spanish speakers, collected from real conversations on a messaging app.</p></td>
+<td><p>Valence &amp; arrousal dimensions and 7 emotions: happiness, disgust, anger, surprise, fear, sadness, and neutral.</p></td>
+<td><p>Audio</p></td>
+<td><p>–</p></td>
+<td><p>Spanish</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2403.02167">EMOVOME Database: Advancing Emotion Recognition in Speech Beyond Staged Scenarios</a></p></td>
+<td><p>Partially open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="http://www.openslr.org/136/">EMNS</a></p></td>
+<td><p>2023</p></td>
+<td><p>1206 high quality labeled utterances by one female speaker (2-3 hours).</p></td>
+<td><p>Anger, excitement, disgust, happiness, surprise, sadness, and neutral (plus sarcasm)</p></td>
+<td><p>Audio</p></td>
+<td><p>0.042 GB</p></td>
+<td><p>English (British)</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2305.13137">EMNS /Imz/ Corpus: An emotive single-speaker dataset for narrative storytelling in games, television and graphic novels</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://apache.org/licenses/LICENSE-2.0">Apache 2.0</a></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://rds.westernsydney.edu.au/Institutes/MARCS/2024/Christopher_Davis/">CAVES</a></p></td>
+<td><p>2023</p></td>
+<td><p>Full hd visual recordings of 10 native cantonese speakers uttering 50 sentences.</p></td>
+<td><p>Anger, happiness, sadness, surprise, fear, disgust and neutral</p></td>
+<td><p>Audio</p></td>
+<td><p>47 GB</p></td>
+<td><p>Chinese (cantonese)</p></td>
+<td><p><a class="reference external" href="https://link.springer.com/article/10.3758/s13428-023-02270-7">A Cantonese Audio-Visual Emotional Speech (CAVES) dataset</a></p></td>
+<td><p>Open</p></td>
+<td><p>Available for research purposes only</p></td>
+</tr>
 <tr class="row-even"><td><p><a class="reference external" href="https://data.mendeley.com/datasets/rdwn4bs5ky/2">BANSpEmo</a></p></td>
 <td><p>2023</p></td>
 <td><p>792 utterance recordings from 22 unprofessional speakers (11 males and 11 females) of six basic emotional reactions of two sets of sentences.</p></td>
@@ -278,7 +322,18 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/records/6345107">Kannada</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://data.mendeley.com/datasets/t9h6p943xy/3">B-SER</a></p></td>
+<td><p>2022</p></td>
+<td><p>1224 speech-audio recordings by 34 non-professional participating actors (17 male and 17 female) from diverse age groups between 19 and 47 years.</p></td>
+<td><p>angry, happy, sad and surprise</p></td>
+<td><p>Audio</p></td>
+<td><p>0.363 GB</p></td>
+<td><p>Bangla</p></td>
+<td><p>–</p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/records/6345107">Kannada</a></p></td>
 <td><p>2022</p></td>
 <td><p>468 audio samples, six different sentences, pronounced by thirteen people (four male and nine female), in five basic emotions plus one neutral emotion</p></td>
 <td><p>Anger, Sadness, Surprise, Happiness, Fear, Neutral</p></td>
@@ -289,6 +344,86 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
 </tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://figshare.com/articles/media/Quechua_Collao_for_Speech_Emotion_Recognition/20292516">Quechua-SER</a></p></td>
+<td><p>2022</p></td>
+<td><p>12420 audio recordings (~15 hours) and their transcriptions by 7 native speakers.</p></td>
+<td><p>Emotional labels using dimensions: valence, arousal, and dominance.</p></td>
+<td><p>Audio</p></td>
+<td><p>3.53 GB</p></td>
+<td><p>Quechua Collao</p></td>
+<td><p><a class="reference external" href="https://www.nature.com/articles/s41597-022-01855-9">A speech corpus of Quechua Collao for automatic dimensional emotion recognition</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://data.mendeley.com/datasets/cy34mh68j9/5">MESD</a></p></td>
+<td><p>2022</p></td>
+<td><p>864 audio files of single-word emotional utterances with Mexican cultural shaping.</p></td>
+<td><p>6 emotions provides single-word utterances for anger, disgust, fear, happiness, neutral, and sadness.</p></td>
+<td><p>Audio</p></td>
+<td><p>0.097 GB</p></td>
+<td><p>Spanish (Mexican)</p></td>
+<td><p><a class="reference external" href="https://pubmed.ncbi.nlm.nih.gov/34891601/">The Mexican Emotional Speech Database (MESD): elaboration and assessment based on machine learning</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/6573016#.ZAjy_9LMJpj">SyntAct</a></p></td>
+<td><p>2022</p></td>
+<td><p>Synthesized database with 997 utterances of three basic emotions and neutral expression based on rule-based manipulation for a diphone synthesizer which we release to the public</p></td>
+<td><p>6 emotions: angry, bored, happy, neutral, sad and scared</p></td>
+<td><p>Audio</p></td>
+<td><p>0.941 GB</p></td>
+<td><p>German</p></td>
+<td><p><a class="reference external" href="http://felix.syntheticspeech.de/publications/synthetic_database.pdf">SyntAct: A Synthesized Database of Basic Emotions</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0">CC BY-SA 4.0</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://drive.google.com/drive/folders/1EKuWH8q178QOtFUYaNohdkZbBHQYAmhL">BEAT</a></p></td>
+<td><p>2022</p></td>
+<td><p>76-Hour and 30-Speaker of 4 different languages: English (60h), Chinese (12h), Spanish (2h) and Japanese (2h).</p></td>
+<td><p>8 emotions: happiness, anger, disgust, sadness, contempt, surprise, fear, and neutral</p></td>
+<td><p>Audio, Video</p></td>
+<td><p>42 GB</p></td>
+<td><p>English, Chinese, Spanish, Japanese</p></td>
+<td><p><a class="reference external" href="https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136670605.pdf">A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis</a></p></td>
+<td><p>Open</p></td>
+<td><p>Non-commercial license</p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://github.com/salute-developers/golos/tree/master/dusha">Dusha</a></p></td>
+<td><p>2022</p></td>
+<td><blockquote>
+<div><p>300 000 audio recordings (~350 hours) of Russian speech, their transcripts and emotiomal labels. The dataset has two subsets: acted and real-life</p>
+</div></blockquote>
+</td>
+<td><p>4 emotions: angry, happy, sad and neutral. Arousal and valence metrics are also available.</p></td>
+<td><p>Audio</p></td>
+<td><p>58 GB</p></td>
+<td><p>Russian</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2212.12266">Large Raw Emotional Dataset with Aggregation Mechanism</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://github.com/salute-developers/golos/blob/master/license/en_us.pdf">Public license with attribution and conditions reserved</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://mafw-database.github.io/MAFW/">MAFW</a></p></td>
+<td><p>2022</p></td>
+<td><p>10045 video-audio clips in the wild.</p></td>
+<td><p>11 single-label emotion categories (anger, disgust, fear, happiness, neutral, sadness, surprise, contempt, anxiety, helplessness, and disappointment) and 32 multi-label emotion categories.</p></td>
+<td><p>Audio, Video</p></td>
+<td><p>–</p></td>
+<td><p>–</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2208.00847">MAFW: A Large-scale, Multi-modal, Compound Affective Database for Dynamic Facial Expression Recognition in the Wild</a></p></td>
+<td><p>Restricted</p></td>
+<td><p>Non-commercial research purposes</p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://viem-ccy.github.io/EMOVIE/dataset_release.html">EMOVIE</a></p></td>
+<td><p>2021</p></td>
+<td><p>9724 samples with audio files and its emotion human-labeled annotation.</p></td>
+<td><p>Polarity metrics (positive:+1, negative:-1)</p></td>
+<td><p>Audio</p></td>
+<td><p>0.572 GB</p></td>
+<td><p>Chinese (Mandarin)</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2106.09317">EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/2.0/legalcode">CC BY-NC-SA 2.0</a></p></td>
+</tr>
 <tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/records/5427549">emoUERJ</a></p></td>
 <td><p>2021</p></td>
 <td><p>Ten sentences from eight actors, equally divided between genders, and they were free to choose the phrases for record audios in four emotions (377 audios).</p></td>
@@ -300,6 +435,28 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
 </tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/records/5525023">Thorsten-Voice Dataset 2021.06 emotional</a></p></td>
+<td><p>2021</p></td>
+<td><p>2400 normalized mono recordings by one person (Thorsten Müller) representing 300 sentences.</p></td>
+<td><p>Amusement, Disgust Anger, Suprise and Neutral (plus drunk, whispering and sleepy states)</p></td>
+<td><p>Audio</p></td>
+<td><p>0.399 GB</p></td>
+<td><p>German</p></td>
+<td><p>–</p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/publicdomain/zero/1.0/">CC0: Public Domain</a></p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://github.com/Ethio2021/ASED_V1">ASED</a></p></td>
+<td><p>2021</p></td>
+<td><p>2474 recordings by 65 participants (25 females and 40 males)). Recordings were judged and rejected according to the opionion of eight judges.</p></td>
+<td><p>Five emotions: anger, happiness, fear, sadness and neutral</p></td>
+<td><p>Audio</p></td>
+<td><p>0.135 GB</p></td>
+<td><p>Amharic</p></td>
+<td><p><a class="reference external" href="https://dl.acm.org/doi/10.1145/3529759">A New Amharic Speech Emotion Dataset and Classification Benchmark</a></p></td>
+<td><p>Open</p></td>
+<td><p>–</p></td>
+</tr>
 <tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/records/5793223">ESCorpus-PE</a></p></td>
 <td><p>2021</p></td>
 <td><p>Spanish peruvian speech gathered from Spanish interviews, TV reports, political debate and testimonials. It contains 3749 utterances, 80 speakers (44 male and 36 female), created from Youtube audios</p></td>
@@ -333,40 +490,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/publicdomain/zero/1.0/">CC0: Public Domain</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://figshare.com/articles/media/Quechua_Collao_for_Speech_Emotion_Recognition/20292516">Quechua-SER</a></p></td>
-<td><p>2022</p></td>
-<td><p>12420 audio recordings (~15 hours) and their transcriptions by 7 native speakers.</p></td>
-<td><p>Emotional labels using dimensions: valence, arousal, and dominance.</p></td>
-<td><p>Audio</p></td>
-<td><p>3.53 GB</p></td>
-<td><p>Quechua Collao</p></td>
-<td><p><a class="reference external" href="https://www.nature.com/articles/s41597-022-01855-9">A speech corpus of Quechua Collao for automatic dimensional emotion recognition</a></p></td>
-<td><p>Open</p></td>
-<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
-</tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://data.mendeley.com/datasets/cy34mh68j9/5">MESD</a></p></td>
-<td><p>2022</p></td>
-<td><p>864 audio files of single-word emotional utterances with Mexican cultural shaping.</p></td>
-<td><p>6 emotions provides single-word utterances for anger, disgust, fear, happiness, neutral, and sadness.</p></td>
-<td><p>Audio</p></td>
-<td><p>0.097 GB</p></td>
-<td><p>Spanish (Mexican)</p></td>
-<td><p><a class="reference external" href="https://pubmed.ncbi.nlm.nih.gov/34891601/">The Mexican Emotional Speech Database (MESD): elaboration and assessment based on machine learning</a></p></td>
-<td><p>Open</p></td>
-<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
-</tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/6573016#.ZAjy_9LMJpj">SyntAct</a></p></td>
-<td><p>2022</p></td>
-<td><p>Synthesized database of three basic emotions and neutral expression based on rule-based manipulation for a diphone synthesizer which we release to the public</p></td>
-<td><p>997 utterances including 6 emotions: angry, bored, happy, neutral, sad and scared</p></td>
-<td><p>Audio</p></td>
-<td><p>0.941 GB</p></td>
-<td><p>German</p></td>
-<td><p><a class="reference external" href="http://felix.syntheticspeech.de/publications/synthetic_database.pdf">SyntAct: A Synthesized Database of Basic Emotions</a></p></td>
-<td><p>Open</p></td>
-<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0">CC BY-SA 4.0</a></p></td>
-</tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://github.com/tobefans/LSSED">LSSED</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://github.com/tobefans/LSSED">LSSED</a></p></td>
 <td><p>2021</p></td>
 <td><p>LSSED: A Large-Scale Dataset and Benchmark for Speech Emotion Recognition</p></td>
 <td><p>Anger, happiness, sadness, disappointment, boredom, disgust, excitement, fear, surprise, normal, and other.</p></td>
@@ -377,7 +501,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p><a class="reference external" href="https://github.com/tobefans/LSSED/blob/main/EULA.pdf">-</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.kaggle.com/datasets/jesusrequena/mlend-spoken-numerals">MLEnd</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.kaggle.com/datasets/jesusrequena/mlend-spoken-numerals">MLEnd</a></p></td>
 <td><p>2021</p></td>
 <td><p>~32700 audio recordings files produced by 154 speakers. Each audio recording corresponds to one English numeral (from “zero” to “billion”)</p></td>
 <td><p>Intonations: neutral, bored, excited and question</p></td>
@@ -388,7 +512,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>Unknown</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://www.kaggle.com/datasets/dejolilandry/asvpesdspeech-nonspeech-emotional-utterances">ASVP-ESD</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://www.kaggle.com/datasets/dejolilandry/asvpesdspeech-nonspeech-emotional-utterances">ASVP-ESD</a></p></td>
 <td><p>2021</p></td>
 <td><p>~13285 audio files collected from movies, tv shows and youtube containing speech and non-speech.</p></td>
 <td><p>12 different natural emotions (boredom, neutral, happiness, sadness, anger, fear, surprise, disgust, excitement, pleasure, pain, disappointment) with 2 levels of intensity.</p></td>
@@ -399,7 +523,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>Unknown</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://hltsingapore.github.io/ESD/">ESD</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://hltsingapore.github.io/ESD/">ESD</a></p></td>
 <td><p>2021</p></td>
 <td><p>29 hours, 3500 sentences, by 10 native English speakers and 10 native Chinese speakers.</p></td>
 <td><p>5 emotions: angry, happy, neutral, sad, and surprise.</p></td>
@@ -410,7 +534,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>Academic License</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/4134758">MuSe-CAR</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/4134758">MuSe-CAR</a></p></td>
 <td><p>2021</p></td>
 <td><p>40 hours, 6,000+ recordings of 25,000+ sentences by 70+ English speakers (see db link for details).</p></td>
 <td><p>continuous emotion dimensions characterized using valence, arousal, and trustworthiness.</p></td>
@@ -421,7 +545,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Academic License &amp; Commercial License</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://github.com/vistec-AI/dataset-releases/releases/tag/v1">THAI SER</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://github.com/vistec-AI/dataset-releases/releases/tag/v1">THAI SER</a></p></td>
 <td><p>2021</p></td>
 <td><p>The recordings are 41 hours, 36 minutes long (27,854 utterances), and were performed by 200 professional actors (112 female, 88 male).</p></td>
 <td><p>5 main emotions assigned to actors: Neutral, Anger, Happiness, Sadness, and Frustration.</p></td>
@@ -432,7 +556,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-sa/4.0">CC BY-SA 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/records/4405783#.Yqjq_9JBxph">French Emotional Speech Database - Oréau</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/records/4405783#.Yqjq_9JBxph">French Emotional Speech Database - Oréau</a></p></td>
 <td><p>2020</p></td>
 <td><p>79 utterances with 10 to 13 utterances pro emotion by 32 non-professional speakers.</p></td>
 <td><p>7 emotions: sadness, anger, disgust, fear, surprise, joy, neutral.</p></td>
@@ -443,7 +567,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="http://www.openslr.org/88/">Att-HACK</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="http://www.openslr.org/88/">Att-HACK</a></p></td>
 <td><p>2020</p></td>
 <td><p>25 speakers interpreting 100 utterances in 4 social attitudes, with 3-5 repetitions each per attitude for a total of around 30 hours of speech.</p></td>
 <td><p>expressive speech in French, 100 phrases with multiple versions (3 to 5) in four social attitudes (friendly, distant, dominant and seductive).</p></td>
@@ -454,7 +578,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Podcast.html">MSP-Podcast corpus</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Podcast.html">MSP-Podcast corpus</a></p></td>
 <td><p>2020</p></td>
 <td><p>100 hours by over 100 speakers (see db link for details).</p></td>
 <td><p>This corpus is annotated with emotional labels using attribute-based descriptors (activation, dominance and valence) and categorical labels (anger, happiness, sadness, disgust, surprised, fear, contempt, neutral and other).</p></td>
@@ -465,6 +589,17 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Academic License &amp; Commercial License</p></td>
 </tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.openslr.org/93/">AISHELL-3</a></p></td>
+<td><p>2020</p></td>
+<td><p>Roughly 85 hours of emotion-neutral recordings spoken by 218 native Chinese mandarin speakers and total 88035 utterances.</p></td>
+<td><p>Neutral</p></td>
+<td><p>Audio</p></td>
+<td><p>19 GB</p></td>
+<td><p>Chinese (Mandarin)</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/2010.11567">AISHELL-3: A Multi-speaker Mandarin TTS Corpus and the Baselines</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://apache.org/licenses/LICENSE-2.0">Apache 2.0</a></p></td>
+</tr>
 <tr class="row-even"><td><p><a class="reference external" href="https://doi.org/10.6084/m9.figshare.12498033">BEASC</a></p></td>
 <td><p>2020</p></td>
 <td><p>Bangla Emotional Audio-Speech Corpus</p></td>
@@ -520,6 +655,28 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></p></td>
 </tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://engineering.jhu.edu/nsa/vesus/">VESUS</a></p></td>
+<td><p>2019</p></td>
+<td><p>252 distinct phrases, each read by 10 actors totalling 6 hours of speech.</p></td>
+<td><p>5 emotions: anger, happiness, sadness, fear and neutral.</p></td>
+<td><p>Audio</p></td>
+<td><p>–</p></td>
+<td><p>English</p></td>
+<td><p><a class="reference external" href="https://engineering.jhu.edu/nsa/wp-content/uploads/2019/10/IS191413.pdf">VESUS: A Crowd-Annotated Database to Study Emotion Production and Perception in Spoken English</a></p></td>
+<td><p>Restricted</p></td>
+<td><p>Academic EULA</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference external" href="https://arxiv.org/abs/2403.02167">Morgan Emotional Speech Set</a></p></td>
+<td><p>2019</p></td>
+<td><p>999 spontaneous voice messages from 100 Spanish speakers, collected from real conversations on a messaging app.</p></td>
+<td><p>Valence &amp; arrousal dimensions and 4 emotions: happiness, anger, sadness, and calmness.</p></td>
+<td><p>Audio</p></td>
+<td><p>0.192 GB</p></td>
+<td><p>English</p></td>
+<td><p><a class="reference external" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203525/">Categorical and Dimensional Ratings of Emotional Speech: Behavioral Findings From the Morgan Emotional Speech Set</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
+</tr>
 <tr class="row-odd"><td><p><a class="reference external" href="https://github.com/HuiZhangDB/PMEmo">PMEmo</a></p></td>
 <td><p>2019</p></td>
 <td><p>Dataset containing emotion annotations of 794 songs as well as the simultaneous electrodermal activity (EDA) signals. A Music Emotion Experiment was well-designed for collecting the affective-annotated music corpus of high quality, which recruited 457 subjects.</p></td>
@@ -597,7 +754,18 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>–</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/1188976#.XrC7a5NKjOR">RAVDESS</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/">OMG Emotion</a></p></td>
+<td><p>2018</p></td>
+<td><p>420 relatively long emotion videos with an average length of 1 minute, collected from a variety of Youtube channels.</p></td>
+<td><p>7 emotions:anger, disgust, fear, happy, sad, surprise and neutral. Plus valence, arousal.</p></td>
+<td><p>Audio, Video</p></td>
+<td><p>–</p></td>
+<td><p>English</p></td>
+<td><p><a class="reference external" href="https://arxiv.org/abs/1803.05434">The OMG-Emotion Behavior Dataset</a></p></td>
+<td><p>Open</p></td>
+<td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/3.0/">CC BY-NC-SA 3.0</a></p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/1188976#.XrC7a5NKjOR">RAVDESS</a></p></td>
 <td><p>2018</p></td>
 <td><p>7356 recordings by 24 actors.</p></td>
 <td><p>7 emotions: calm, happy, sad, angry, fearful, surprise, and disgust</p></td>
@@ -608,7 +776,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://www.kaggle.com/tli725/jl-corpus">JL corpus</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://www.kaggle.com/tli725/jl-corpus">JL corpus</a></p></td>
 <td><p>2018</p></td>
 <td><p>2400 recording of 240 sentences by 4 actors (2 males and 2 females).</p></td>
 <td><p>5 primary emotions: angry, sad, neutral, happy, excited. 5 secondary emotions: anxious, apologetic, pensive, worried, enthusiastic.</p></td>
@@ -619,7 +787,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/1478765">CaFE</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/1478765">CaFE</a></p></td>
 <td><p>2018</p></td>
 <td><p>6 different sentences by 12 speakers (6 fmelaes + 6 males).</p></td>
 <td><p>7 emotions: happy, sad, angry, fearful, surprise, disgust and neutral. Each emotion is acted in 2 different intensities.</p></td>
@@ -630,7 +798,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/1326428">EmoFilm</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/1326428">EmoFilm</a></p></td>
 <td><p>2018</p></td>
 <td><p>1115 audio instances sentences extracted from various films.</p></td>
 <td><p>5 emotions: anger, contempt, happiness, fear, and sadness.</p></td>
@@ -641,7 +809,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>EULA: End User License Agreement</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.kaggle.com/suso172/arabic-natural-audio-dataset">ANAD</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.kaggle.com/suso172/arabic-natural-audio-dataset">ANAD</a></p></td>
 <td><p>2018</p></td>
 <td><p>1384 recording by multiple speakers.</p></td>
 <td><p>3 emotions: angry, happy, surprised.</p></td>
@@ -652,7 +820,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://zenodo.org/record/3727593">EmoSynth</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://zenodo.org/record/3727593">EmoSynth</a></p></td>
 <td><p>2018</p></td>
 <td><p>144 audio file labelled by 40 listeners.</p></td>
 <td><p>Emotion (no speech) defined in regard of valence and arousal.</p></td>
@@ -663,7 +831,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.amir-zadeh.com/datasets">CMU-MOSEI</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.amir-zadeh.com/datasets">CMU-MOSEI</a></p></td>
 <td><p>2018</p></td>
 <td><p>65 hours of annotated video from more than 1000 speakers and 250 topics.</p></td>
 <td><p>6 Emotion (happiness, sadness, anger,fear, disgust, surprise) + Likert scale.</p></td>
@@ -674,7 +842,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://github.com/A2Zadeh/CMU-MultimodalSDK/blob/master/LICENSE.txt">CMU-MOSEI License</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://sites.google.com/view/verbodatabase/home">VERBO</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://sites.google.com/view/verbodatabase/home">VERBO</a></p></td>
 <td><p>2018</p></td>
 <td><p>14 different phrases by 12 speakers (6 female + 6 male) for a total of 1167 recordings.</p></td>
 <td><p>7 emotions: Happiness, Disgust, Fear, Neutral, Anger, Surprise, Sadness</p></td>
@@ -685,7 +853,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Available for research purposes only</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.amir-zadeh.com/datasets">CMU-MOSI</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.amir-zadeh.com/datasets">CMU-MOSI</a></p></td>
 <td><p>2017</p></td>
 <td><p>2199 opinion utterances with annotated sentiment.</p></td>
 <td><p>Sentiment annotated between very negative to very positive in seven Likert steps.</p></td>
@@ -696,7 +864,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://github.com/A2Zadeh/CMU-MultimodalSDK/blob/master/LICENSE.txt">CMU-MOSI License</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Improv.html">MSP-IMPROV</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://ecs.utdallas.edu/research/researchlabs/msp-lab/MSP-Improv.html">MSP-IMPROV</a></p></td>
 <td><p>2017</p></td>
 <td><p>20 sentences by 12 actors.</p></td>
 <td><p>4 emotions: angry, sad, happy, neutral, other, without agreement</p></td>
@@ -707,7 +875,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Academic License &amp; Commercial License</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://github.com/CheyneyComputerScience/CREMA-D">CREMA-D</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://github.com/CheyneyComputerScience/CREMA-D">CREMA-D</a></p></td>
 <td><p>2017</p></td>
 <td><p>7442 clip of 12 sentences spoken by 91 actors (48 males and 43 females).</p></td>
 <td><p>6 emotions: angry, disgusted, fearful, happy, neutral, and sad</p></td>
@@ -718,7 +886,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://github.com/CheyneyComputerScience/CREMA-D/blob/master/LICENSE.txt">Open Database License &amp; Database Content License</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://espace.library.uq.edu.au/view/UQ:446541">Example emotion videos used in investigation of emotion perception in schizophrenia</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://espace.library.uq.edu.au/view/UQ:446541">Example emotion videos used in investigation of emotion perception in schizophrenia</a></p></td>
 <td><p>2017</p></td>
 <td><p>6 videos:Two example videos from each emotion category (angry, happy and neutral) by one female speaker.</p></td>
 <td><p>3 emotions: angry, happy and neutral.</p></td>
@@ -729,7 +897,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions">Permitted Non-commercial Re-use with Acknowledgment</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="http://voice.fub.it/activities/corpora/emovo/index.html">EMOVO</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="http://voice.fub.it/activities/corpora/emovo/index.html">EMOVO</a></p></td>
 <td><p>2014</p></td>
 <td><p>6 actors  who  played  14  sentences.</p></td>
 <td><p>6 emotions: disgust, fear, anger, joy, surprise, sadness.</p></td>
@@ -740,7 +908,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>–</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://diuf.unifr.ch/main/diva/recola/download.html">RECOLA</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://diuf.unifr.ch/main/diva/recola/download.html">RECOLA</a></p></td>
 <td><p>2013</p></td>
 <td><p>3.8 hours of recordings by 46 participants.</p></td>
 <td><p>negative and positive sentiment (valence and arousal).</p></td>
@@ -751,7 +919,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Academic License &amp; Commercial License</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.unige.ch/cisa/gemep">GEMEP corpus</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.unige.ch/cisa/gemep">GEMEP corpus</a></p></td>
 <td><p>2012</p></td>
 <td><p>Videos10 actors portraying 10 states.</p></td>
 <td><p>12 emotions: amusement, anxiety, cold anger (irritation), despair, hot anger (rage),  fear (panic), interest, joy (elation), pleasure(sensory), pride, relief, and sadness. Plus, 5 additional emotions: admiration, contempt, disgust, surprise, and tenderness.</p></td>
@@ -762,7 +930,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>–</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://sites.google.com/site/ogcorpus/home/en">OGVC</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://sites.google.com/site/ogcorpus/home/en">OGVC</a></p></td>
 <td><p>2012</p></td>
 <td><p>9114 spontaneous utterances and 2656 acted utterances by 4 professional actors (two male and two female).</p></td>
 <td><p>9 emotional states: fear, surprise, sadness, disgust, anger, anticipation, joy, acceptance and the neutral state.</p></td>
@@ -773,7 +941,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>–</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://www.ultes.eu/ressources/lego-spoken-dialogue-corpus/">LEGO corpus</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://www.ultes.eu/ressources/lego-spoken-dialogue-corpus/">LEGO corpus</a></p></td>
 <td><p>2012</p></td>
 <td><p>347 dialogs with 9,083 system-user exchanges.</p></td>
 <td><p>Emotions classified as garbage, non-angry, slightly angry and very angry.</p></td>
@@ -784,7 +952,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>License available with the data. Free of charges for research purposes only.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://semaine-db.eu/">SEMAINE</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://semaine-db.eu/">SEMAINE</a></p></td>
 <td><p>2012</p></td>
 <td><p>95 dyadic conversations from 21 subjects. Each subject converses with another playing one of four characters with emotions.</p></td>
 <td><p>5 FeelTrace annotations: activation, valence, dominance, power, intensity</p></td>
@@ -795,7 +963,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Academic EULA</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="http://kahlan.eps.surrey.ac.uk/savee/Database.html">SAVEE</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="http://kahlan.eps.surrey.ac.uk/savee/Database.html">SAVEE</a></p></td>
 <td><p>2011</p></td>
 <td><p>480 British English utterances by 4 males actors.</p></td>
 <td><p>7 emotions: anger, disgust, fear, happiness, sadness, surprise and neutral.</p></td>
@@ -806,7 +974,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Free of charges for research purposes only.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://tspace.library.utoronto.ca/handle/1807/24487">TESS</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://tspace.library.utoronto.ca/handle/1807/24487">TESS</a></p></td>
 <td><p>2010</p></td>
 <td><p>2800 recording by 2 actresses.</p></td>
 <td><p>7 emotions: anger, disgust, fear, happiness, pleasant surprise, sadness, and neutral.</p></td>
@@ -817,7 +985,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND 4.0</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="https://metashare.ut.ee/repository/download/4d42d7a8463411e2a6e4005056b40024a19021a316b54b7fb707757d43d1a889/">EEKK</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="https://metashare.ut.ee/repository/download/4d42d7a8463411e2a6e4005056b40024a19021a316b54b7fb707757d43d1a889/">EEKK</a></p></td>
 <td><p>2007</p></td>
 <td><p>26 text passage read by 10 speakers.</p></td>
 <td><p>4 main emotions: joy, sadness, anger and neutral.</p></td>
@@ -828,7 +996,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p><a class="reference external" href="https://metashare.ut.ee/repository/download/4d42d7a8463411e2a6e4005056b40024a19021a316b54b7fb707757d43d1a889/">CC-BY license</a></p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="https://sail.usc.edu/iemocap/iemocap_release.htm">IEMOCAP</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="https://sail.usc.edu/iemocap/iemocap_release.htm">IEMOCAP</a></p></td>
 <td><p>2007</p></td>
 <td><p>12 hours of audiovisual data by 10 actors in 5 sessions.</p></td>
 <td><p>Full: neutral state; happiness; sadness; anger; surprise; fear; disgust; frustration; excited; other. Balance 5 emotions: happiness, anger, sadness, frustration and neutral. Three dimensions: valence, arousal, dominance</p></td>
@@ -839,7 +1007,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p><a class="reference external" href="https://sail.usc.edu/iemocap/Data_Release_Form_IEMOCAP.pdf">IEMOCAP license</a></p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="http://research.nii.ac.jp/src/en/Keio-ESD.html">Keio-ESD</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="http://research.nii.ac.jp/src/en/Keio-ESD.html">Keio-ESD</a></p></td>
 <td><p>2006</p></td>
 <td><p>A set of human speech with vocal emotion spoken by a Japanese male speaker.</p></td>
 <td><p>47 emotions including angry, joyful, disgusting, downgrading, funny,  worried, gentle, relief, indignation, shameful, etc.</p></td>
@@ -850,7 +1018,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Restricted</p></td>
 <td><p>Available for research purposes only.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="http://emodb.bilderbar.info/index-1280.html">EMO-DB</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="http://emodb.bilderbar.info/index-1280.html">EMO-DB</a></p></td>
 <td><p>2005</p></td>
 <td><p>800 recording spoken by 10 actors (5 males and 5 females).</p></td>
 <td><p>7 emotions: anger, neutral, fear, boredom, happiness, sadness, disgust.</p></td>
@@ -861,7 +1029,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>–</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference external" href="http://www.enterface.net/enterface05/docs/results/databases/project2_database.zip">eNTERFACE05</a></p></td>
+<tr class="row-odd"><td><p><a class="reference external" href="http://www.enterface.net/enterface05/docs/results/databases/project2_database.zip">eNTERFACE05</a></p></td>
 <td><p>2005</p></td>
 <td><p>Videos by 42 subjects, coming from 14 different nationalities.</p></td>
 <td><p>6 emotions: anger, fear, surprise, happiness, sadness and disgust.</p></td>
@@ -872,7 +1040,7 @@ <h1>Datasets<a class="headerlink" href="#datasets" title="Permalink to this head
 <td><p>Open</p></td>
 <td><p>Free of charges for research purposes only.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference external" href="http://kom.aau.dk/~tb/speech/Emotions/">DES</a></p></td>
+<tr class="row-even"><td><p><a class="reference external" href="http://kom.aau.dk/~tb/speech/Emotions/">DES</a></p></td>
 <td><p>2002</p></td>
 <td><p>4 speakers (2 males and 2 females).</p></td>
 <td><p>5 emotions: neutral,  surprise,  happiness,  sadness  and  anger</p></td>
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