sound processing Flashcards

1
Q

sound features

A

volume, loudness, frequency, pitch

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2
Q

frequency domain

A

representation of a signal based on how much information is contained at diefferent frequencies

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3
Q

harmonics

A

component frequencies of a fundamental frequency

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4
Q

Fourier series coefficient for k=0

A

DC component

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5
Q

what is the maximum frequency that can be detected using FFT

A

the Nyquist frequency = Fs/2

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6
Q

spectogram

A

visual representation of the spectrum of frequencies of a signal as they vary with time

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7
Q

noise

A

all unwanted signals contaminating the useful signal

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8
Q

filter

A

a system designed to maximise the useful signal, while removing the noise

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9
Q

finite impulse response

A

type of digital filter in signal processing that has a finite duration response to an input signal

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10
Q

infinite impulse response

A

have an impulse response that extends infinitely into the past and future

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11
Q

random or white noise

A

manifested by small fluctuations in the measured signal values

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12
Q

frequency response

A

describes how its output amplitude and phase change with respect to different input frequencies

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13
Q

passband

A

refers to the frequencies that passed

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14
Q

stopband

A

refers to the frequencies that are blocked

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15
Q

transition band

A

refers to the frequencies that in between passed and blocked

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16
Q

cutoff frequency

A

division between transition and band and passband

17
Q

filters in time domain

A

moving average filter

18
Q

moving average filter

19
Q

filters in frequency domain

A

low-pass
high-pass
band-pass
band-reject
Notch filter

20
Q

low-pass filter

A

suppresses the high frequencies

21
Q

high-pass filter

A

lets only high frequencies pass

22
Q

band-pass filter

A

lets only a range of frequencies pass

23
Q

band-reject filter

A

block a range of frequencies

24
Q

Notch filter or narrow band reject filter

A

attenuates several singular frequencies while preserving the rest

25
frequency spectrum analysis
aims to identify which frequencies are present in a time-varying signal, at a given moment
26
Fourier analysis
turn a time-varying signal into a frequency-varying signal
27
Fourier series
mathematical representation that allows a periodic signal to be expressed as the sum of an infinite series of sinusoidal functions
28
Fourier coeffiecent
tell us which frequency is present in the signal and to what extent
29
What part of the FFT vector is useful?
only the first half, because the second half is a mirror of the first