Software Output Interpretation

Python Data Processing Basics for Acoustic Analysis

November 12, 2024
Amber Galvano
by Amber Galvano. Interested in learning how to merge data and metadata from multiple sources into a consolidated dataset? Dealing with annotated audio and want to automate your workflow? Tried Praat scripting but want something more streamlined? This blog post will walk through some key domain-specific Python-based tools you will need in order to take your audio data, annotations, and speaker metadata and come away with a tabular dataset containing acoustic measures, ready to visualize and submit to statistical analysis. This tutorial uses acoustic phonetics data, but can be adapted to a range of projects involving repeated measures data and/or work with audio files.

Valeria Ramírez Castañeda

Data Science for Social Justice Fellow (2024-2025)
Integrative Biology

Valeria Ramírez Castañeda is a Colombian biologist currently pursuing a PhD in the Department of Integrative Biology at the University of California, Berkeley. I completed my undergraduate degree in Biology at the National University of Colombia and earned a master's degree in Ecology and Evolution, as well as another in Science Communication. During her PhD, she is studying the interactions between snakes and frogs and how this influences the evolution of toxin resistance in snakes. She is also collaborating and leading projects regarding the consequences of English in science and the...

Theo Snow

Availability: By appointment only

Consulting Areas: Python, R, SQL, SAS, Databases & SQL, Data Manipulation and Cleaning, Data Science, Data Visualization, Geospatial Data, Maps & Spatial Analysis, Machine Learning, Mixed Methods, Qualitative methods, Surveys, Sampling & Interviews, Regression Analysis, Means Tests, Software Output Interpretation, Other, Excel, Git or Github, RStudio, RStudio Cloud, SAS, Tableau

Anusha Bishop

Availability: By appointment only

Consulting Areas: Python, R, Cloud & HPC Computing, Data Sources, Data Visualization, Geospatial Data, Maps & Analysis, Machine Learning, Research Design, Cluster analysis, Experimental design, Hierarchical Models, High dimensional statistics, Means Tests, Nonparametric methods, Regression Analysis, Software Output Interpretation, Spatial statistics, Bash or Command Line, Excel, Git or Github, RStudio

Nikita Samarin

Instructor
Electrical Engineering and Computer Science (EECS)

Nikita Samarin is a doctoral student in Computer Science in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley advised by Serge Egelman and David Wagner. His research focuses on computer security and privacy from an interdisciplinary perspective, combining approaches from human-computer interaction, behavioral sciences, and legal studies. Samarin is a member of the Berkeley Lab for Usable and Experimental Security (BLUES) and an affiliated graduate researcher at the Center for Long-Term Cybersecurity (CLTC) and the...

Sohail Khan

Data Science Fellow 2024-2025
School of Information

Hey everyone, I’m Sohail - a 1st years Master’s student studying Data Science at the I-School. I am interested in the intersection between Computer Science, Data Science, and Cognitive Psychology and using these tools to understand, discover, and drive the development of assistive technologies.

I have experience building with brain computer Interfaces, developing distributed data processing applications, and am currently working on a large scale archival project aimed at preserving the history and memory of resistance movements through an embedding based...

Yue Lin

Data Science Fellow 2024-2025
Political Science

Yue is a Ph.D. student in Political Science at the University of California, Berkeley, with a Designated Emphasis on Political Economy. Using mixed methods, she studies foreign lobbying, geopolitical risk, and economic security to understand when, how, and why multinational corporations become the targets and weapons of state power rivalry.

Alex Stephenson

Senior Data Science Fellow
Political Science

I am a Ph.D. Student in the Travers Department of Political Science. My primary research interests are military organizations, policing, the determinants of political violence, and causal inference. I am also interested in creating tools to make software easier to use for non-technical political scientists.

Amanda Glazer

Instructor
Statistics

Amanda is a PhD candidate in the statistics department at Berkeley. Her research focuses on causal inference with applications in education, political science and sports. Previously she earned her Bachelor’s degree in mathematics and statistics, with a secondary in computer science, from Harvard.

Enrique Valencia López

Data Science Fellow
Graduate School of Education

Enrique Valencia López is a PhD student in the Policy, Politics and Leadership cluster at the Graduate School of Education.His research interests relate to three broad areas: the stratification of education by gender, immigration status and ethnicity; the measurement of teacher working conditions and well-being; and education in Latin America.

Before coming to Berkeley, Enrique worked for Mexico’s National Institute for Educational Evaluation and Assessment (INEE) in both the Policy and Indicators area. During that time, he co-authored Mexico’s first report on the educational...