landmarks
google-landmarkshow2sign-asl-landmarks
How2Sign ASL Landmarks
Sentence-level MediaPipe landmark cache for the How2Sign ASL translation dataset. This dataset stores preprocessed landmark arrays only, not MP4 clips.
The rows come from the local How2Sign realigned CSV files and front-view raw videos. Each successful row is one sentence segment sampled at a 25 FPS cap and stored in compressed NPZ shards.
Why This Dataset Exists
The public How2Sign data has known alignment/completeness issues: some text rows do not… See the full description on the dataset page: https://huggingface.co/datasets/martinctl/how2sign-asl-landmarks.how2sign-landmarks-front-raw-parquet
Split
Count
train
31047
validation
1739
test
2343
Parquet-shared front mediapipe data from PSewmuthu/How2Sign_Holistic
import cv2
import numpy as np
import tempfile
import os
from datasets import load_dataset
from IPython.display import Video, display
# 1. Initialize Streams
print("Initializing streams...")
landmark_stream = load_dataset("bdanko/how2sign-landmarks-front-raw-parquet", split="train", streaming=True)
rgb_stream =… See the full description on the dataset page: https://huggingface.co/datasets/bdanko/how2sign-landmarks-front-raw-parquet.Level-5-Cultures-Landmarks-1vtl-speech-landmarks
VTL Speech Landmarks Dataset
Articulatory speech synthesis dataset with acoustic landmarks, generated using VocalTractLab (VTL).
Dataset Description
This dataset contains synthesized speech for 117,497 English words from the CMU Pronouncing Dictionary, generated with two speakers (male and female). Each word includes:
Audio: 48kHz WAV files
Landmarks: Acoustic-phonetic event markers (JSON)
Articulatory data: Full vocal tract trajectories from VTL (JSON)
Speakers… See the full description on the dataset page: https://huggingface.co/datasets/mcamara/vtl-speech-landmarks.google_landmarks_places
Google Landmarks places
Google Landmarks is a great dataset, but it lacks geospatial information about the places. This dataset fills
this gap by providing latitude and longitude for each landmark. The dataset also contains the name of the landmark from OpenStreetMap
and information about the country, the province/state, and the city/village where the landmark is located. This information was collected from OSM
via Nominatim.