The Zpoken team was invited to support the holding of fair parliamentary elections in Georgia 2020.
The general goal of the project was monitoring of Georgian parliamentary elections that took place in October, 2020. The main purpose of the project was to monitor and prevent so-called Carousel voting, that involves “busloads of voters driven around to cast ballots multiple times”. That is, organized groups of voters, using fake passports, move from one pooling station to another by bus, voting for the specific candidate multiple times. …
Let’s say you want to create your own ASR dataset. You gathered some audios and texts of variable lengths, but STT models require relatively short audios to be trained on. Few minutes long audio is already too long and requires slicing. The possible solution is audio to text aligning.
This tutorial explains how to align long audios with their texts not using any complex or heavyweight programs for Forced Alignment. Prerequisite is some STT model capable of generating decent text (with timestamps) to align with our existing labels (transcriptions).
This article describes part of the project of monitoring the parliamentary elections in Georgia in 2020. The main goal of the project was to find forgers — people voting several times (at different voting stations) in the online regime. There was a volunteer capturing all voters on election day at most of the voting stations. To reach the goal we needed to train a lightweight embedder that could identify repeating persons in different backgrounds, captured with different devices.