Mumospee V2: A MUltiMOdal SPEEch Corpus
Dataset Description
Mumospee v2 is a large-scale multimodal speech dataset containing audio and video recordings with transcripts, aggregated from:
- European Council events — official speeches, interviews, and doorstep appearances.
- Public YouTube meetings — webinars, conferences, panel discussions, and institutional videos.
This release is built upon the first version of the Mumospee dataset, significantly expanding both the scale and diversity of content, and unifying audio and video data into a consistent metadata format suitable for large-scale speech and multimodal research.
The original Mumospee v1 dataset is available at:
👉 https://huggingface.co/datasets/meetween/mumospee
The dataset is designed for research in speech recognition, multimodal modeling, meeting analysis, and AI-driven content understanding.
All media are referenced via source URLs; no audio or video files are redistributed. Transcripts and metadata are included.
Dataset Structure
| Column | Type | Description |
|---|---|---|
audio_url |
string | URL to audio |
video_url |
string | URL to video |
duration |
float | Duration in seconds |
language |
string | Primary spoken language |
transcript |
string (JSON) | Full transcript as JSON-encoded array of segments. Each segment contains language, start_seconds, end_seconds, and text fields with time-aligned transcription data. |
split |
string | Source tag (EU_Council or YouTube_Meeting) |
license |
string | License information for the content |
attribution |
string (JSON) | Attribution as required by the license |
Statistic Summary
The dataset is provided as two subsets: eu_council and youtube_meeting.
| Source / Tag | Number of Records | Total Duration (hours) | Average Duration (hours) |
|---|---|---|---|
| eu_council | 45,411 | 3,665.68 | 0.0807 |
| youTube_meeting | 122,407 | 80,127.65 | 0.6546 |
Language Distribution
The table below reports the primary spoken language per recording.
| Language | EU_Council Count | EU_Council Duration (hours) | YouTube_Meeting Count | YouTube_Meeting Duration (hours) |
|---|---|---|---|---|
| English | 23635 | 1754.21 | 95896 | 59568.38 |
| German | 3582 | 294.16 | 1467 | 831.99 |
| French | 2953 | 240.68 | 8222 | 5910.38 |
| Spanish | 2427 | 230.31 | 11382 | 9497.5 |
| Italian | 1374 | 122.0 | 1471 | 1092.87 |
| Portuguese | 1230 | 113.16 | 3030 | 2706.79 |
| Swedish | 1092 | 96.51 | 82 | 49.71 |
| Dutch | 1064 | 97.09 | 782 | 418.2 |
| Polish | 970 | 91.22 | 29 | 24.79 |
| Czech | 873 | 77.6 | 13 | 8.19 |
| Croatian | 826 | 71.11 | 2 | 2.96 |
| Danish | 787 | 71.06 | 5 | 0.95 |
| Slovak | 684 | 62.17 | 1 | 1.15 |
| Finnish | 647 | 62.9 | 5 | 5.36 |
| Greek | 604 | 37.16 | 13 | 4.87 |
| Slovenian | 519 | 40.49 | 0 | 0.0 |
| Bulgarian | 401 | 66.11 | 2 | 0.62 |
| Hungarian | 384 | 34.39 | 2 | 0.48 |
| Luxembourgish | 297 | 28.92 | 0 | 0.0 |
| Romanian | 295 | 25.66 | 1 | 0.07 |
| Maltese | 156 | 5.63 | 0 | 0.0 |
| Lithuanian | 92 | 5.32 | 0 | 0.0 |
| Arabic | 79 | 4.53 | 0 | 0.0 |
| Latvian | 73 | 5.18 | 0 | 0.0 |
| Ukrainian | 56 | 4.48 | 0 | 0.0 |
| Russian | 38 | 2.67 | 0 | 0.0 |
| Estonian | 37 | 2.36 | 0 | 0.0 |
| Serbian | 36 | 2.84 | 0 | 0.0 |
| Georgian | 33 | 1.99 | 0 | 0.0 |
| Norwegian | 29 | 2.98 | 0 | 0.0 |
| Albanian | 25 | 1.89 | 0 | 0.0 |
| Macedonian | 23 | 1.78 | 0 | 0.0 |
| Bosnian | 17 | 1.36 | 0 | 0.0 |
| Montenegrin | 16 | 1.09 | 0 | 0.0 |
| Turkish | 14 | 1.37 | 0 | 0.0 |
| Belarusian | 6 | 0.31 | 0 | 0.0 |
| Moldavian | 5 | 0.34 | 0 | 0.0 |
| Catalan | 4 | 0.41 | 0 | 0.0 |
| Persian | 4 | 0.36 | 0 | 0.0 |
| Japanese | 4 | 0.25 | 0 | 0.0 |
| Indonesian | 3 | 0.25 | 0 | 0.0 |
| Vietnamese | 3 | 0.33 | 0 | 0.0 |
| Chinese | 3 | 0.28 | 0 | 0.0 |
| Armenian | 3 | 0.07 | 0 | 0.0 |
| Korean | 3 | 0.33 | 0 | 0.0 |
| Hindi | 1 | 0.1 | 0 | 0.0 |
| Kazakh | 1 | 0.1 | 0 | 0.0 |
| Khmer | 1 | 0.06 | 0 | 0.0 |
| Tajik | 1 | 0.09 | 0 | 0.0 |
| Swahili | 1 | 0.05 | 0 | 0.0 |
Notes on Transcripts
EU Council (audio & video): Transcripts are generated using the Whisper ASR package and are not official EU transcripts. Each entry contains one or more languages per recording, corresponding to the full speech.
YouTube Meeting (video):
Transcripts are extracted from YouTube subtitle tracks. They may be auto-generated or user-uploaded, marked in the metadata. Transcript quality may therefore vary.
Usage
from datasets import load_dataset
# Load the dataset in streaming mode (recommended for large datasets)
dataset = load_dataset("meetween/mumospee_v2", streaming=True)
# Access first row of from eu_council set
first_row = next(iter(dataset["eu_council"]))
print("Transcript:", first_row["transcript"])
print("Audio URL:", first_row["audio_url"])
print("Video URL:", first_row["video_url"])
print("Language:", first_row["language"])
print("Duration (s):", first_row["duration"])
# Iterate over the first 5 examples
for i, example in enumerate(dataset["eu_council"]):
print(f"{i+1}. {example['language']} - {example['duration']}s")
print(f"Transcript snippet: {example['transcript'][:100]}...\n")
if i >= 4:
break
# Access audio or video URLs
first_example = next(iter(dataset["eu_council"]))
print("Listen to audio:", first_example["audio_url"])
print("Watch video:", first_example["video_url"])
Licensing Information
YouTube CC-BY:
All YouTube content in Mumospee v2 is selected from videos marked with the Creative Commons Attribution (CC BY) license. CC BY permits reuse, transformation, and training uses as long as proper attribution is maintained (e.g., title, uploader, source URL). Users must comply with the CC BY terms when accessing media via URLs. Creative Commons
European Council reuse notice:
Council of the EU content is published with a copyright notice stating that reproduction is authorised provided the original source is acknowledged and the meaning is not distorted. Mumospee distributes derived metadata and signal information only; raw media remains at the source and is accessed by URL. European Council
Users must comply with the source license or notice when accessing or reusing media via URLs.
Intended Use and Data Quality
Mumospee v2 is intended for speech and multimodal research, including speech recognition, meeting analysis, and language understanding. The current dataset includes metadata and filtered based on LLM prompting. As such, some videos may be incorrectly labeled for meetings or have misidentified languages. In future releases we will incorporate audio and video analysis pipelines to refine classification and release timestamped segments for downstream tasks.
- Downloads last month
- 119