Topics

Data adequacy and acoustic features
Voice Signal Processing

Learning Objectives

By the end of this lesson, you will be able to:

Analyze the adequacy of data for the unique feature extraction for voice (pitch, intensity, duration and formants)
Introduce basic principles of digital signal processing (DSP) as applied to voice signals. Discuss techniques for noise reduction, signal filtering and feature extraction, with focus on importance of preprocessing voice data for analysis.

Learning Content

How Can I Use This?

Physiology of Voice: Understanding where a voice signal comes from and how it is used is essential for working effectively with voice data. This includes analyzing whether the data is adequate for extracting unique voice features such as pitch, intensity, duration, and formants.

By understanding how a voice signal is generated, you can assess whether your goals are feasible. If you need specific information from the data, this knowledge helps you determine whether it is present and usable, ensuring a more informed approach to voice analysis. Additionally, recognizing the connection between voice production and signal processing strengthens your ability to work with voice-based applications.

Voice Signal Processing: This section builds on James’ discussion of voice physiology and how voice data enters the computer, shifting focus to what happens next. It covers the mathematical and conceptual foundations needed to work with voice data, helping you understand the features you’ll be working with and what computations you may need to perform. Additionally, it explains how these features are extracted from the dataset, ensuring you can effectively interpret and utilize them in your analysis.