pilot7747/VoxDIY
This repository provides data and code for "Vox Populi, Vox DIY: Benchmark Dataset for Crowdsourced Audio Transcription" paper.
This project provides datasets and tools for evaluating and improving crowdsourced audio transcriptions. It helps you assess the quality of transcripts submitted by multiple workers for the same audio files, and can help you create robust new audio datasets with validated human input. Data consists of audio files, individual crowd worker transcriptions, and their corresponding ground-truth texts. It's intended for researchers and practitioners working on speech-to-text technologies or managing crowdsourcing annotation projects.
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Use this if you need to evaluate the accuracy of transcriptions from a crowd of workers against a known 'ground truth' or synthesize speech for creating new transcription tasks.
Not ideal if you're looking for a simple, out-of-the-box solution to transcribe audio without involving a crowdsourcing workflow or human quality control.
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Python
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Last pushed
Jul 22, 2021
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