Available at: https://digitalcommons.calpoly.edu/theses/2771
Date of Award
3-2024
Degree Name
MS in Computer Science
Department/Program
Computer Science
College
College of Engineering
Advisor
Foaad Khosmood
Advisor Department
Computer Science
Advisor College
College of Engineering
Abstract
Digital Democracy is a CalMatters and California Polytechnic State University initia-
tive to promote transparency in state government by increasing access to the Califor-
nia legislature. While Digital Democracy is made up of many resources, one founda-
tional step of the project is obtaining accurate, timely transcripts of California Senate
and Assembly hearings. The information extracted from these transcripts provides
crucial data for subsequent steps in the pipeline. In the context of Digital Democracy,
upleveling is when humans verify, correct, and annotate the transcript results after
the legislative hearings have been automatically transcribed. The upleveling process
is done with the assistance of a software application called the Transcription Tool.
The human upleveling process is the most costly and time-consuming step of the Dig-
ital Democracy pipeline. In this thesis, we hypothesize that we can make significant
reductions to the time needed for upleveling by using Natural Language Processing
(NLP) systems and techniques. The main contribution of this thesis is engineering
a new automatic transcription pipeline. Specifically, this thesis integrates a new au-
tomatic speech recognition service, a new speaker diarization model, additional text
post-processing changes, and a new process for speaker identification. To evaluate the system’s improvements, we measure the accuracy and speed of the newly integrated features and record editor upleveling time both before and after the additions.