datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sqp-tts-en
SQP TTS (English)
Synthesized speech for SQPsychConv_qwen-2.5, a synthetic CBT therapist-client
dialogue dataset (English).
Each configuration below corresponds to one TTS model. Load a single model
with:
from datasets import load_dataset
ds = load_dataset("sinselm/sqp-tts-en", "qwen3-tts")
Models included
qwen3-tts: https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base
cosyvoice: https://huggingface.co/FunAudioLLM/Fun-CosyVoice3-0.5B-2512
fishaudio:… See the full description on the dataset page: https://huggingface.co/datasets/marleen-snsl/sqp-tts-en.moral-number-corpus
A Perspectivist Corpus of Numbers in Social Judgements
This is the dataset for A Perspectivist Corpus of Numbers in Social Judgements.
We constructed a corpus of moral and social judgements (questions are derived from the Commonsense Norm Bank) that asks people to fill in number ranges that do not change a given judgement.
Our corpus was crowdsourced from 30 annotators and contains 898 statements for a total of 3k annotations.
This work adds to available moral and social judgement… See the full description on the dataset page: https://huggingface.co/datasets/Marlon154/moral-number-corpus.annomi-tts-en
AnnoMI TTS (English)
Synthesized speech for the AnnoMI motivational interviewing dialogues (English).
Each configuration below corresponds to one TTS model. Load a single model
with:
from datasets import load_dataset
ds = load_dataset("sinselm/annomi-tts-en", "qwen3-tts")
Models included
qwen3-tts: https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base
cosyvoice: https://huggingface.co/FunAudioLLM/Fun-CosyVoice3-0.5B-2512
fishaudio:… See the full description on the dataset page: https://huggingface.co/datasets/marleen-snsl/annomi-tts-en.dr-marl-papers
Distributionally-Robust RL & Cooperative MARL — top-tier paper index
A hand-reviewed index of 1,989 papers on distributionally-robust reinforcement learning
and cooperative multi-agent RL, drawn from a complete harvest of 75,819 accepted papers
at ICML, NeurIPS, ICLR, AAMAS and AISTATS (2010–2026).
Every candidate that survived the keyword filter was read and labelled one by one — 2,979
papers — rather than accepting an automatic classifier's output.
Buckets… See the full description on the dataset page: https://huggingface.co/datasets/Ngseo/dr-marl-papers.alpacoFutures_202306_202312Future dada on FG and sc.
historic-trading-dataobras-emmanuel