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24.910 Topics in Linguistic Theory: Laboratory Phonology
Spring 2007
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24.910
Laboratory Phonology
Basic Audition
• No class next week (Tuesday is a Monday)
• Readings for 2/27: Johnson chs 5 & 6
• Assignments (due 2/27):
– Basic acoustics.
– VOT and laryngeal contrasts in Mandarin and
English.
Audition
Outer Ear
Middle
Ear
Inner Ear
Anvil
Ear Flap
Auditory
Nerve
Hammer
Ear Canal
Eardrum
Cochlea
Stirrup
Eustachian Tube
Figure by MIT OpenCourseWare.
Anatomy
Audition
• Loudness
• Pitch
• ‘Auditory spectrograms’
Loudness
• The perceived loudness of a sound depends on the
amplitude of the pressure fluctuations in the sound
wave.
• Amplitude is usually measured in terms of rootmean-square (rms amplitude):
– The square root of the mean of the squared amplitude
over some time window.
rms amplitude
•
•
•
Square each sample in the analysis window.
Calculate the mean value of the squared waveform:
– Sum the values of the samples and divide by the number of
samples.
Take the square root of the mean.
1.5
1
0.5
0
0
0.05
0.1
-0.5
-1
-1.5
time
0.15
0.2
pressure
pressure^2
rms amplitude
rms amplitude
0
.01
Time in seconds
.02
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith. Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Intensity
• Perceived loudness is more closely related to intensity
(power per unit area), which is proportional to the square
of the amplitude.
• relative intensity in Bels = log10(x2/r2)
• relative intensity in dB = 10 log10(x2/r2)
= 20 log10(x/r)
• In absolute intensity measurements, the comparison
amplitude is usually 20μPa, the lowest audible pressure
fluctuation of a 1000 Hz tone (dB SPL).
logarithmic scales
• log xn = n log x
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
0
10
20
30
x
40
50
Loudness
• The relationship between intensity and perceived loudness
is not exactly logarithmic.
20
100
18
90
80
dB SPL
14
70
12
60
Sones
10
50
8
40
6
30
4
20
2
10
0
0
500,000
1,000,000
1,500,000
dB SPL
Sones
16
0
2,000,000
Pressure (µPa)
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith. Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Loudness
• Loudness also depends on frequency.
• equal loudness contours for pure tones:
Source: Wikimedia Commons.
Loudness
• At short durations, loudness also depends on duration.
• Temporal integration: loudness depends on energy in the
signal, integrated over a time window.
• Duration of integration is often said to be about 200ms, i.e.
relevant to the perceived loudness of vowels.
Pitch
• Perceived pitch is approximately linear with respect to
frequency from 100-1000 Hz, between 1000-10,000 Hz the
relationship is approximately logarithmic.
24
Frequency (Bark)
20
16
12
8
4
0
0
1
2
3
4
5
6
7
8
9
10
Frequency (kHz)
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith. Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Pitch
•
•
The non-linear frequency response of the auditory system is related to the
physical structure of the basilar membrane.
basilar membrane ‘uncoiled’:
15,400
8,700
11,500
4,900
6,500
2,700
3,700
1,500
2,000
750
1,100
300
500
100
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith. Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Masking - simultaneous
• Energy at one frequency can reduce audibility of
simultaneous energy at another frequency (masking).
• One sound can also mask a preceding or following sound.
104
Masking
103
102
10
1
400
600
800
1000
1200
1600
2000
2400
2600 3200 3600 4000
Frequency of masked tone
Example of masking of a tone by a tone. The frequency of the masking tone is 1200 Hz. Each curve corresponds to a
different masker level, and gives the amount by which the threshold intensity of the masked tone is multiplied in the
presence of the masker, relative to its threshold in quiet. The dashed lines near 1200 Hz and its harmonics are estimates
of the masking functions in the absence of the effect of beats.
Figure by MIT OpenCourseWare. Adapted from Stevens, Kenneth N. Acoustic Phonetics. Cambridge, MA: MIT Press, 1999. ISBN; 9780262194044.
Time course of auditory nerve response
Response to a noise burst:
• Strong initial response
• Rapid adaptation (~5 ms)
• Slow adaptation (>100ms)
• After tone offset, firing rate
only gradually returns to
spontaneous level.
256
-60
128
0
256
128
-40
0
64
msec
0
128
Figure by MIT OpenCourseWare. Adapted from Kiang et al. (1965)
Interactions between sequential sounds
• A preceding sound can affect the auditory nerve response
to a following tone (Delgutte 1980).
Discharge rate (SP/S)
600
NO AT
TT = 27 dB SPL
AT = 13 dB SPL
AT = 37 dB SPL
400
200
0
0
200
400
M
0
400
M
200
AT
0
200
400
M
TT
Figure by MIT OpenCourseWare. Adapted from Stevens, Kenneth N. Acoustic Phonetics. Cambridge, MA: MIT Press, 1999. ISBN: 9780262194044,
after Delgutte, B. "Representation of Speech-like Sounds in the Discharge Patterns of Auditory-nerve Fibers."
Journal of the Acoustical Society of America 68, no. 3 (1980): 843-857.
Auditory ‘spectrograms’
The auditory system performs a running frequency analysis of
acoustic signals - cf. spectrogram.
• A regular spectrogram analyzes frequency of equal widths,
but the peripheral auditory system analyzes frequency bands
that are wider at higher frequencies.
• Further disparities are introduced by the non-linearities of the
peripheral auditory system, e.g.
– loudness is non-linearly related to intensity
– masking(simultaneous and nonsimultaneous)
85
80
Vowel /I/
75
Auditory Frequency (Bark)
240
0
2
4
6
8
10
12
14
16
18
20
22
24
65
60
55
220
50
200
Amplitude (dB)
Level, dB
70
45
180
40
160
0
500
1,000
1,500
2,000
2,500 3,000
3,500
4,000
Frequency, Hz
140
120
Image by MIT OpenCourseWare. Adapted from Moore, Brian. The
Handbook of Phonetic Science. Edited by William J. Hardcastle and John Laver.
Malden, MA: Blackwell, 1997. ISBN: 9780631188483.
100
80
0
2
4
6
Acoustic Frequency (kHz)
8
10
A comparison of acoustic (light line) and auditory (heavy line) spectra of a complex wave
composed of sine waves at 500 at 1,500 Hz. Both spectra extend from 0 to 10 kHz, although
on different frequency scales. The auditory spectrum was calculated from the acoustic spectrum
using the model described in Johnson (1989).
80
Vowel /I/
70
80
Image by MIT OpenCourseWare. Adapted from Johnson, Keith. Acoustic and Auditory
Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Excitation Level, dB
60
50
40
50
30
20
10
2
4
6
8
10
12
14
16
18
20
22
24
26
Number of ERBs, E
The spectrum of a synthetic vowel /I/ (top) plotted on a linear frequency scale,
and the excitation patterns for that vowel (bottom) for two overall levels, 50 and
80 dB. The excitation patterns are plotted on an ERB scale.
Image by MIT OpenCourseWare. Adapted from Moore, Brian. The Handbook
of Phonetic Science. Edited by William J. Hardcastle and John Laver.
Malden, MA: Blackwell, 1997. ISBN: 9780631188483.
Spectrogram images removed due to copyright restrictions.
Figure 3.8 in Johnson, Keith. "Comparison of Normal Acoustic Spectrogram and Auditory Spectrogram or Cochleagram."
Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Italian vowels
F2 (Hz)
2500
2300
2100
1900
1700
1500
1300
1100
900
700
500
200
i
e
u
o

400

600
a
800
ERB scales
F2 (E)
25
23
21
19
17
15
6
8
10
E(F1)
12
14
16
24.910
Linguistic Phonetics
Analog-to-digital conversion of
speech signals
2.0
1.6
1.2
0.8
0.4
0.0
-0.4
-0.8
-1.2
0.00
0.01
0.02
0.03
0.04
0.05
0.04
0.05
The Results Of Sampling
2.0
1.6
1.2
0.8
0.4
0.0
-0.4
-0.8
-1.2
0.00
0.01
0.02
0.03
Figure by MIT OpenCourseWare.
Analog-to-digital conversion
• Almost all acoustic analysis is now computer-based.
• Sound waves are analog (or continuous) signals, but digital
computers require a digital representation - i.e. a series of
numbers, each with a finite number of digits.
• There are two continuous scales that must be divided into
discrete steps in analog-to-digital conversion of speech: time
and pressure (or voltage).
– Dividing time into discrete chunks is called sampling.
– Dividing the amplitude scale into discrete steps is called
quantization.
Sampling
• The amplitude of the analog
signal is sampled at regular
intervals.
• The sampling rate is measured
in Hz (samples per second).
• The higher the sampling rate,
the more accurate the digital
representation will be.
(a)
0
Time
.01
.02
.03 Sec
A wave with a fundamental frequency of 100 Hz and a major
component at 300Hz sampled at 1500Hz.
(b)
0
Time
.01
.02
.03 Sec
The same wave sampled at 600 Hz.
(c)
0
Time
.01
.02
.03 Sec
Figure by MIT OpenCourseWare. Adapted from Ladefoged, Peter.
L104/204 Phonetic Theory lecture notes, University of California, Los Angeles.
Sampling
•
•
In order to represent a wave
component of a given frequency, it
is necessary to sample the signal
with at least twice that frequency
(the Nyquist Theorem).
The highest frequency that can be
represented at a given sampling rate
is called the Nyquist frequency.
(a)
0
Time
.01
.02
.03 Sec
A wave with a fundamental frequency of 100 Hz and a major
component at 300Hz sampled at 1500Hz.
(b)
•
The wave at right has a significant
harmonic at 300 Hz
– (a) sampling rate 1500 Hz
– (b) sampling rate 600 Hz
– (c) sampling rate 500 Hz
0
Time
.01
.02
.03 Sec
The same wave sampled at 600 Hz.
(c)
0
Time
.01
.02
.03 Sec
Figure by MIT OpenCourseWare. Adapted from Ladefoged, Peter.
L104/204 Phonetic Theory lecture notes, University of California, Los Angeles.
What sampling rate should you use?
• The highest frequency that (young, undamaged) ears can
perceive is about 20 kHz, so to ensure that all audible
frequencies are represented we must sample at 2×20 kHz =
40 kHz.
• The ear is relatively insensitive to frequencies above 10
kHz, and almost all of the information relevant to speech
sounds is below 10 kHz, so high quality sound is still
obtained at a sampling rate of 20 kHz.
• There is a practical trade-off between fidelity of the signal
and memory, but memory is getting cheaper all the time.
What sampling rate should you use?
• For some purposes (e.g. measuring vowel formants), a high
sampling rate can be a liability, but it is always possible to
downsample before performing an analysis.
• Audio CD uses a sampling rate of 44.1 kHz.
• Many A-to-D systems only operate at fractions of this rate
(22050 Hz, 11025 Hz).
Aliasing
Amplitude
• Components if a signal which are above the Nyquist
frequency are misrepresented as lower frequency
components (aliasing).
• To avoid aliasing, a signal must be filtered to eliminate
frequencies above the Nyquist frequency.
• Since practical filters are not infinitely sharp, this will
attenuate energy near to the Nyquist frequency also.
0
2
4
Time (ms)
6
8
10
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith.
Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Quantization
• The amplitude of the signal at each sampling point must be
specified digitally - quantization.
• Divide the continuous amplitude scale into a finite number
of steps. The more levels we use, the more accurately we
approximate the analog signal.
Amplitude
20 steps
200 steps
0
5
10
Time (ms)
15
20
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith.
Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Quantization
• The number of levels is specified in terms of the number of
bits used to encode the amplitude at each sample.
– Using n bits we can distinguish 2n levels of amplitude.
– e.g. 8 bits, 256 levels.
– 16 bits, 65536 levels.
• Now that memory is cheap, speech is almost always
digitized at 16 bits (the CD standard).
Quantization
Amplitude
• Quantizing an analog signal necessarily introduces
quantization errors.
• If the signal level is lower, the degradation in signal-tonoise ratio introduced by quantization noise will be greater,
so digitize recordings at as high a level as possible without
exceeding the maximum amplitude that can be represented
(clipping).
• On the other hand, it is essential to avoid clipping.
0
5
10
15
Time (ms)
20
25
Figure by MIT OpenCourseWare. Adapted from Johnson, Keith.
Acoustic and Auditory Phonetics. Malden, MA: Blackwell Publishers, 1997. ISBN: 9780631188483.
Voicing and aspiration
• Many languages make a contrast between two sets of stops
with different laryngeal properties, loosely referred to as
‘voiced’ and ‘voiceless’.
• The precise details of these laryngeal contrasts differ from
language to language.
• Some broad distinctions:
– voiced [b]: vocal fold vibration during closure
• bal (‘hair’)
– voiceless unaspirated [p]: no vibration of the vocal
folds, short VOT
• pal (‘take care of’)
– voiceless aspirated [pʰ]: no vibration of the vocal folds,
long VOT (high airflow after release)
• pal (‘knife blade’)
Listen to all three sound files here.
Voicing and aspiration
• Voiced vs.voiceless [b vs. p]
– Russian, French, Dutch
• Unaspirated vs. aspirated [p vs. pʰ]
– Mandarin, Cantonese
• Voiced vs. voiceless unaspirated vs. aspirated [b vs. p vs.
pʰ]
– Hindi, Thai
• English shows contextual variation between
voicing and aspiration.
Voice Onset Time
• English utterance-initial stops
Voiceless unaspirated
Voiceless aspirated
22 ms
0.3268
0.1853
0
0
–0.471
1.1154
5000
86 ms
1.27558
Time (s)
0
1.1154
1.27558
Time (s)
die
–0.3718
4.26614
5000
4.42706
Time (s)
0
4.26614
4.42706
Time (s)
tie
VOT, closure voicing
• English intervocalic stops can be fully voiced
– VOT is 0 ms in 2nd and 3rd stops
0.2644
0
–0.1468
547.195
5000
547.485
Time (s)
0
547.195
547.485
Time (s)
brigadoo(n)
VOT, closure voicing
• Hindi - three-way contrast
– recordings from Ladefoged
http://www.phonetics.ucla.edu/vowels/chapter12/hindi.html
0.494
0.3851
0.2819
0
0
0
–0.4972
0
5000
Time (s)
0
0
–0.4971
0
0.231127
5000
0.231127
Time (s)
Time (s)
–0.475
0
0.113588
5000
0
0
0.113588
0.13828
Time (s)
0
0
0.13828
bal
Time (s)
Time (s)
pal
pʰal
‘hair’
‘take care of’
‘knife blade’
Listen to all three sound files here.