datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
suno-ai-music-dataset
Suno AI Music Dataset (Multi-Genre Curated)
A human-curated, multi-genre audio dataset generated with Suno V5.5 (chirp-fenix), covering 100+ sub-sub-genres across electronic, hip-hop, Latin, jazz, world, rock, ambient, pop, reggae, and classical music. Each track ships with full audio (MP3), cover art, the original generation prompt, and a 32-column metadata schema designed for downstream audio-ML research.
This is not a "scrape everything Suno produces" dump. It is a… See the full description on the dataset page: https://huggingface.co/datasets/Kukedlc/suno-ai-music-dataset.MANGO
MANGO: A Corpus of Human Ratings for Speech
MANGO (MUSHRA Assessment corpus using Native listeners and Guidelines to understand human Opinions at scale) is the first large-scale dataset designed for evaluating Text-to-Speech (TTS) systems in Indian languages.
Key Features:
255,150 human ratings of TTS-generated outputs and ground-truth human speech.
Covers two major Indian languages: Hindi & Tamil, and English.
Based on the MUSHRA (Multiple Stimuli with Hidden Reference… See the full description on the dataset page: https://huggingface.co/datasets/ai4bharat/MANGO.maleo-short-1.5H
Dataset Card for Maleo Short 1.5H
Dataset Description
Dataset Summary
Maleo Short 1.5H is a manually curated, rigorously annotated speaker diarization dataset designed to benchmark State-of-the-Art (SOTA) models against complex, "in-the-wild" media domains. While modern diarization pipelines excel in controlled acoustic environments (like telephony or reading corpora), they heavily struggle with the overlapping speech, sound effects, and rapid speaker shifts… See the full description on the dataset page: https://huggingface.co/datasets/maleo-ai/maleo-short-1.5H.LMD-AI-Detection
LMD AI-Generated Music Detection Benchmark
(Note: The corresponding research paper will be released later.)
Dataset Description
The rapid advancement of AI music generation has raised growing concerns about the authenticity of digital music. While deepfake detection has been extensively studied in the audio domain, symbolic music (MIDI) remains largely unexplored.
This dataset presents a comprehensive benchmark for AI-generated symbolic music detection, examining… See the full description on the dataset page: https://huggingface.co/datasets/dhlee3000/LMD-AI-Detection.pulmonary-disease-airway-lung-function-dataset
Acoustic Waveform Airway and Respiratory Examination (AWARE/PTEase) Dataset
Guidelines
AWARE/PTEase is a smartphone-based sensing system that examines human airway's internal physiological conditions, developed by the Intelligent Systems Laboratory at University of Pittsburgh. AWARE/PTEase probes the airway with acoustic pulses through mouth, and collect the airway's reflections for analysis. Please refer to our paper and github repo for more details.
This dataset… See the full description on the dataset page: https://huggingface.co/datasets/ericyxy98/pulmonary-disease-airway-lung-function-dataset.jalak
Jalak — Indonesian Multi-Speaker TTS Dataset
A Coqui-TTS-ready multi-speaker speech dataset for Indonesian, Javanese, and Sundanese,
built to accompany the maiaid/jalak-model VITS
checkpoint.
The layout matches jalak-model/config.json exactly: root dataset/ path, Coqui coqui
formatter, pipe-separated metadata audio_file|text|speaker_name.
Dataset Summary
Split / metadata file
Speakers
Clips
Source
License
metadata-javanese.csv
39 × JV-xxxxx
5,822… See the full description on the dataset page: https://huggingface.co/datasets/maleo-ai/jalak.knesset-plenums
About
This dataset is derived from raw a/v recordings and human-generated protocols of the Knesset (the Israeli house of representatives) plenums as part of the ivrit.ai project.
Consider visiting the preview space for this dataset here
Method
Data dumps from the Knesset contain A/V recordings, alongside proprietary protocols with timestamps.
We extract the audio stream, and clean up timestamp mistakes (such as backward jumps, or out-of-order timestamp artifacts).
The… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/knesset-plenums.crowd-recital-yi
About
This dataset was created by crowd-sourced recording sessions in Yiddish as part of the ivrit.ai Crowd Recital project.
Volunteers read on normal desktop or mobile setting Wikipedia articles while time-stamping every sentence read.
Later this data is normalized by aligning the gathered captions with the audio using Stable Whisper (See Below).
The recording project is an ongoing effort and new data will be appended to this dataset periodically as it is being generated.… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/crowd-recital-yi.crowd-whatsapp-yi
About
This dataset was created by crowd-sourced Whatsapp voice recordings in Yiddish as part of the ivrit.ai project.
Volunteers read a message sent to them from a predefined set of messages, recording themselves using Whasapp voice message sent to the collecting bot.
Later this data is normalized by aligning the captions with the audio using Stable Whisper (See Below).
The recording project is an ongoing effort and new data will be appended to this dataset periodically as it is… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/crowd-whatsapp-yi.luel-multilingual-tts-samples
Multilingual TTS Samples (Luel)
License: All Rights Reserved. Proprietary. Access only for authorized parties; no redistribution or use without permission. See LICENSE.
A multilingual text-to-speech / read-speech dataset of short scripted utterances across 7 languages. Each sample is a single-speaker recording of a written prompt, paired with rich speaker and recording metadata. Useful for TTS training and evaluation, ASR adaptation, dialect/accent studies, and read-speech… See the full description on the dataset page: https://huggingface.co/datasets/Luel-ai/luel-multilingual-tts-samples.hallym_AI_OpenDataset
Hallym Adult and Child Speech Dataset
This dataset contains speech recordings and transcriptions collected from adult and child speakers for AI-based speech and language research.
Dataset Overview
Total Records: 2,714
Speakers: 49 (adult: 25, child: 24)
Groups: adult, child
File Format: WAV (audio) + TXT (transcription)
Speaker Statistics
Group
Count
Gender
Age Range
Adult
25명
남/여
50~78세
Child
24명
남/여
3~8세
Dataset Fields… See the full description on the dataset page: https://huggingface.co/datasets/K-University-AIED/hallym_AI_OpenDataset.zwesui-grupa-5-it-ai
Wykorzystanie ASR do transkrypcji polskich nagrań o tematyce AI
Korpus do ewaluacji systemów ASR języka polskiego stworzony w ramach warsztatów
Ewaluacja Systemów Rozpoznawania Mowy (UAM WMI, edycja 2026, zespół 5).
Zbiór powstał jako część kursu - publikujemy go publicznie, żeby inni badacze
polskiego ASR mogli z niego korzystać i porównywać wyniki na wspólnym benchmarku.
Cel i pytania badawcze
Cel główny:
Porównanie jakości 3 systemów ASR dla spontanicznej… See the full description on the dataset page: https://huggingface.co/datasets/slapekm/zwesui-grupa-5-it-ai.aitf-dfk3-neutral-audiosaitf-dfk3-audios-dataset