datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
dialogs-ru-emotional-conversations
Dialogs: A Studio-Quality Expressive Conversational Russian Speech Corpus
Dialogs is a 20.6-hour studio-quality corpus of expressive, conversational
Russian speech, designed for dialog-oriented and emotional text-to-speech.
Unlike existing Russian corpora — mostly single-speaker read speech or large but
low-quality web-mined audio — Dialogs was recorded by professional theatre actors
performing scripted dialogs face-to-face, capturing natural turn-taking,
timing, and expressive… See the full description on the dataset page: https://huggingface.co/datasets/langswap/dialogs-ru-emotional-conversations.speech-emotion-recognition
Speech Emotion Recognition
Dataset comprises 30,000+ audio recordings featuring 4 distinct emotions: euphoria, joy, sadness, and surprise. This extensive collection is designed for research in emotion recognition, focusing on the nuances of emotional speech and the subtleties of speech signals as individuals vocally express their feelings.
By utilizing this dataset, researchers and developers can enhance their understanding of sentiment analysis and improve automatic speech… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/speech-emotion-recognition.arabic-multidialect-emotional-speech-demo
DataHive AI — Demo: Arabic Multi-Dialect Emotional Speech
A DataHive AI dataset: a stratified 1-hour demo sample from a full corpus of 50+ hours. We can also create larger audio datasets upon client request.
Most public Arabic speech corpora flatten dialect into a single label and ignore emotion entirely. This corpus does the opposite: every recording is tagged with one of four regional Arabic dialects (Najdi, Hejazi, Jordanian, Moroccan) and one of four target emotions (Sad, Happy… See the full description on the dataset page: https://huggingface.co/datasets/datahiveai/arabic-multidialect-emotional-speech-demo.egyption-with-emotion-dataset
Egption Text-Audio Dataset With Emotions and Diarization
Creating datasets for TTS and ASR models with emotions and Diarization
In case you want to focus only one speaker , you can fiter based on speaker_role
Source Code
if you want to collect more data from youtube, you can check this link
🙏 Acknowledgements
This project makes use of the forced alignment model and Cohere ASR model provided by:
MahmoudAshraf/mms-300m-1130-forced-aligner
Cohere ASR
Hubert… See the full description on the dataset page: https://huggingface.co/datasets/OmarAhmedSobhy/egyption-with-emotion-dataset.audio-emotion-detection-dataset
Audio Emotion Detection Dataset
Github: Audio Emotion Detection Dataset
Connect with me : Linkedin
Speech clips in English and Hindi annotated with emotion labels and ASR transcripts.
Audio is sourced from public YouTube videos and trimmed to approximately 60 seconds per clip.
Noise reduction is applied via noisereduce and silero-vad.
Emotions (5 classes)
Label
Description
angry
Aggressive, confrontational speech
calm… See the full description on the dataset page: https://huggingface.co/datasets/RapidOrc121/audio-emotion-detection-dataset.Moroccan-Arabic-Multimodal-Emotion-Recognition
MDER-MA — Moroccan Arabic Multimodal Emotion Recognition (TTS-aligned repackaging)
A repackaging of the MDER-MA dataset that pairs every audio clip with its Arabic (Moroccan dialect / Darija) transcript and ships speaker-disjoint train/validation/test splits.
Original dataset: Ouali, S. & El Garouani, S. (2025). MDER-MA: A multimodal dataset for emotion recognition in low-resource Moroccan Arabic language. Data in Brief. DOI: 10.1016/j.dib.2025.112005. Mendeley:… See the full description on the dataset page: https://huggingface.co/datasets/FatimahEmadEldin/Moroccan-Arabic-Multimodal-Emotion-Recognition.TTS-emotion-voice
TTS Emotion Voice: Unconfident Interview Speech
以台灣華語面試回答文字合成的不自信語音資料集。這是研究用的合成資料，不是真人錄音；
所有 unconfident=1 標籤來自生成 prompt，尚未經完整的人類情緒標註驗證。
兩個設定
config
筆數
取樣率
時長範圍
總時長
用途
max12
471
24 kHz
6.267–12.000 秒
4,636.990 秒
保留較完整語意與韻律的長片段對照組
nnime_match_v2
471
16 kHz
0.256–12.000 秒
1,188.188 秒
匹配 NNIME Train Unconfident 時長分布的硬切消融組
兩個 config 使用相同 471 個來源 parent、相同 U25/U50/U75 成員與 prompt 配置；
U25 包含於 U50，U50 包含於 U75。metadata.csv 的 in_u25、in_u50、in_u75… See the full description on the dataset page: https://huggingface.co/datasets/guan-chen/TTS-emotion-voice.Arabic-Emotional-Audio-Dataset-Baved
BAVED — Basic Arabic Vocal Emotions Dataset (TTS-ready repackaging)
A re-packaged, transcript-aligned version of the Basic Arabic Vocal Emotions Dataset (BAVED) with explicit Arabic transcripts, English glosses, speaker metadata, and speaker-disjoint train/validation/test splits.
Original dataset: Aouf Yacine, Basic Arabic Vocal Emotions Dataset (BAVED), GitHub: https://github.com/40uf411/Basic-Arabic-Vocal-Emotions-Dataset. This repackaging adds metadata; all audio is unchanged.… See the full description on the dataset page: https://huggingface.co/datasets/FatimahEmadEldin/Arabic-Emotional-Audio-Dataset-Baved.audio-emotion-detection-dataset
Audio Emotion Detection Dataset
Github: Audio Emotion Detection Dataset
Connect with me : Linkedin
Speech clips in English and Hindi annotated with emotion labels and ASR transcripts.
Audio is sourced from public YouTube videos and trimmed to approximately 60 seconds per clip.
Noise reduction is applied via noisereduce and silero-vad.
Emotions (5 classes)
Label
Description
angry
Aggressive, confrontational speech
calm… See the full description on the dataset page: https://huggingface.co/datasets/kotangalechaitali9007/audio-emotion-detection-dataset.eng-sports-radio-psst-iu-emotion-splits
English Sports Radio Non-Neutral Emotion IU Splits
Public non-neutral subset of NathanRoll/eng-sports-radio-psst-iu.
Each row is one intonation unit with exactly three columns:
audio: embedded 16 kHz mono audio for the IU
text: a leading emotion special token followed by the Parakeet transcript
accent: broadcast-location proxy accent label
Neutral examples were removed. The remaining rows are split by emotion:
joy: 247 rows, 0.287 audio hours
surprise: 153 rows, 0.188 audio… See the full description on the dataset page: https://huggingface.co/datasets/NathanRoll/eng-sports-radio-psst-iu-emotion-splits.sharif_emotional_speech_dataset
Sharif Emotional Speech Dataset (ShEMO)
Dataset Summary
The dataset includes 3000 semi-natural utterances, equivalent to 3 hours and 25 minutes of speech data extracted from online Persian radio plays. The ShEMO covers speech samples of 87 native-Persian speakers for five basic emotions including anger, fear, happiness, sadness and surprise, as well as neutral state. Twelve annotators label the underlying emotional state of utterances and majority voting is used to decide… See the full description on the dataset page: https://huggingface.co/datasets/pariajm/sharif_emotional_speech_dataset.indian-tts-emotion-60min
indian-tts-emotion-60min
A small, carefully curated text-to-speech dataset: ~68 minutes of clean,
single-speaker-per-clip audio in Indian English (en-IN) and Hindi (hi-IN), sourced
from YouTube, with accurate transcriptions and per-clip emotion/style tags.
Built as a data-quality exercise: clips were filtered conservatively and a sample was
verified by listening rather than shipped straight from an automated pipeline.
Summary
Language
Clips
Duration (min)… See the full description on the dataset page: https://huggingface.co/datasets/sarthwa8/indian-tts-emotion-60min.bedvibe-emotional-speechBedVibe Emotional Speech Dataset
Studio-quality emotional speech dataset
• Preview samples available on Hugging Face
• Full commercial dataset available via BedVibe Studio
• Languages currently available: English, Greek
• Additional languages can be recorded on request
• 6 emotions
• 48 kHz / 32-bit float audio
• Professionally recorded in studio conditions
Studio-recorded emotional speech datasets designed for training text-to-speech systems.
Currently available on our website: more than 108… See the full description on the dataset page: https://huggingface.co/datasets/pan82/bedvibe-emotional-speech.