2: Perception of sound
- Page ID
- 134554
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)In this part of the book, you can expect to learn how to
- distinguish between measurable characteristics of vibrations at the ear and human perception
- describe connections between
- amplitude and loudness perception
- frequency and pitch perception
- spectral content, envelope and timbre perception
- read and interpret sound graphs
- move back and forth between different ways of representing sounds, including
- words
- time-domain graphs (o-scope graphs)
- frequency-domain graphs (FFTs)
- spectrograms
- explain the role of frequency ratios in musical intervals and spectral content
Sound sources- tuning forks, the strings on a guitar, your larynx when you speak, the cone of a stereo speaker- vibrate. These objects push against the nearby air molecules and force them to vibrate. Those molecules push on the molecules near them and so on. The disturbances in the air travel outward in all directions and eventually reach some sort of detector- like a microphone or a human ear. When the air molecules near the detector vibrate, the sound detector often converts the mechanical vibrations in electrical ones that can be recorded and/or processed. Vibrations that reach the human eardrum get turned into electrical impulses that your brain interprets as sound.
The characteristics of vibrations at the ear play a key role in what we hear. This chapter focuses on the link between characteristics of vibrations- like frequency, amplitude and spectral content- and what humans hear.
- 2.1: Subjective impressions
- This page examines human sound perception, covering loudness (strength of sound), pitch (highness or lowness), and timbre (unique tone quality). It emphasizes that these characteristics are subjective impressions rather than exact measurements and stresses the importance of understanding these concepts in the context of auditory experiences.
- 2.2: What drives perception
- This page explains the process through which vibrations detected by the eardrum are translated into sound perception in the brain. It highlights the influence of loudness (linked to amplitude), pitch (based on fundamental frequency), and timbre (resulting from the interplay of amplitude and spectral content) on how sounds are experienced. The discussion also addresses unpitched sounds, illustrating the complexity of human auditory perception.
- 2.3: Frequency and pitch- How do we know?
- This page explores sound's frequency-pitch relationship, showcasing historical inventions like the Savart Wheel and siren disks that demonstrate how vibration frequencies affect musical pitch. It also details practical applications, such as rumble strips and “singing roads,” examining how car speed and bump spacing create sound through specific calculations.
- 2.4: Musical intervals and temperament
- This page covers musical intervals within the equal temperament (ET) system, detailing how it divides the octave into twelve semitones with specific frequency ratios. It provides a formula for calculating frequencies and contrasts ET with non-ET systems regarding interval consistency.
- 2.5: Frequency ratios and pitch perception
- This page explains the structure of the piano keyboard, detailing key arrangement from A to G and the significance of octaves as frequency-based intervals. It emphasizes the logarithmic nature of pitch perception, showing how perceived differences relate to frequency ratios. Additionally, it contrasts linear and logarithmic graphing to clarify frequency relationships, asserting that logarithmic scaling more accurately represents musical intervals.
- 2.6: Interpreting graphs
- This page explains sound graph analysis, including time domain graphs, frequency domain graphs (FFT), and spectrograms. It illustrates how time domain graphs depict loudness changes and help infer pitch. FFTs offer detailed snapshots of spectral content for static sounds, while spectrograms show frequency changes over time. The "Mystery Sound" example of a trombone note demonstrates these concepts, illustrating amplitude increases and the prominence of overtones as the sound evolves.
- 2.7: Perception of sound- Review and homework
- This page covers key terms in sound perception, such as loudness, pitch, and timbre. It poses review questions distinguishing perceived from measurable sound quantities and discusses physical factors influencing perception. Exercises involve analyzing oscilloscope and spectrum graphs to compare sound attributes and their sources, emphasizing the importance of these elements in understanding the relationship between sound characteristics and auditory experiences.
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