MIVIA Road Events Dataset

Dataset Summary

MIVIA_ROAD_DB1 is an annotated audio dataset for road acoustic event detection. 57 scene recordings with precise timestamped annotations for two classes of road sound events. Originally released by the MIVIA Lab, University of Salerno.

Dataset Viewer

The viewer above shows one scene audio file per row. Use MIVIA_events.csv for the full per-event annotation table (400 events total).

Statistics

Scene recordings	57
Total events	400
Class 2 events	200
Class 3 events	200
Audio format	WAV, 32000 Hz, mono
Avg duration	~65–70 seconds

Files

File	Description
data/*.wav	57 scene audio recordings
metadata.csv	Scene-level metadata (powers the viewer)
MIVIA_events.csv	Full event table (400 rows, timestamps per event)
MIVIA_events.json	Same data in JSON format

Columns in MIVIA_events.csv

Column	Description
xml_file	Source annotation XML
scene_audio	Mixed scene WAV file
event_wav	Isolated event sound file
class_id	2 or 3
class_name	Event class name
start_sec	Event start time (seconds)
end_sec	Event end time (seconds)
bg_class_name	Background sound class
bg_pathname	Background audio file

Usage

import pandas as pd
from huggingface_hub import hf_hub_download

# Load full event annotations
csv_path = hf_hub_download(
    repo_id="Titung/MIVIA",
    filename="MIVIA_events.csv",
    repo_type="dataset"
)
df = pd.read_csv(csv_path)
print(df.head())
print(df["class_id"].value_counts())

# Load a scene audio file
from huggingface_hub import hf_hub_download
import librosa

wav_path = hf_hub_download(
    repo_id="Titung/MIVIA",
    filename="data/00001_1.wav",
    repo_type="dataset"
)
y, sr = librosa.load(wav_path, sr=None)

# Slice first event
row = df.iloc[0]
event_audio = y[int(row.start_sec * sr) : int(row.end_sec * sr)]
print(f"Event duration: {len(event_audio)/sr:.2f}s  Class: {row.class_id}")

Citation

Foggia, P., Petkov, N., Saggese, A., Strisciuglio, N., & Vento, M. (2015). Reliable detection of audio events in highly noisy environments. Pattern Recognition Letters. Elsevier.

MIVIA Lab, University of Salerno — http://mivia.unisa.it