Acoustic properties of Anii vowels

Acoustic properties of Anii vowels#

[2]

LING 497 Phonetic Analysis: Articulation, Acoustics, Audition

The Pennsylvania State University

Prof. Deborah Morton

Revised

25 May 2023

Programming Environment#

import pandas as pd

cols=[
  'vowel',
  'word',
  'duration_[s]',
  'avg_pitch_[Hz]',
  'avg_f1_[Hz]',
  'avg_f2_[Hz]',
]

Spectrograms#

[ɪŋʊɾʊ]#

df1 = pd.DataFrame(
  data=[
    ['ɪ','ɪŋʊɾʊ',0.086119,93.59,466.6903022180635,1766.545144534218],
    ['ʊ','ɪŋʊɾʊ',0.097062,98.88,515.24847237277,873.1683246462179],
    ['ʊ','ɪŋʊɾʊ',0.044060,100.40,555.185617008055,1397.6951513926542],
  ],
  columns=cols
)
df1
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 ɪ ɪŋʊɾʊ 0.086119 93.59 466.690302 1766.545145
1 ʊ ɪŋʊɾʊ 0.097062 98.88 515.248472 873.168325
2 ʊ ɪŋʊɾʊ 0.044060 100.40 555.185617 1397.695151

[gɪtɑnɪ]#

df2 = pd.DataFrame(
  data=[
    ['ɪ','gɪtɑnɪ',0.089908,91.83,364.51569821825854,2023.891019658131],
    ['ɑ','gɪtɑnɪ',0.105583,100.10,688.6183713367284,1492.4319104789486],
    ['ɪ','gɪtɑnɪ',0.054948,103.30,479.36615954884286,1835.6777999095636],
  ],
  columns=cols
)
df2
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 ɪ gɪtɑnɪ 0.089908 91.83 364.515698 2023.89102
1 ɑ gɪtɑnɪ 0.105583 100.10 688.618371 1492.43191
2 ɪ gɪtɑnɪ 0.054948 103.30 479.366160 1835.67780

[gʊfɑŋɑ]#

df3 = pd.DataFrame(
  data=[
    ['ʊ','gʊfɑŋɑ',0.066951,102.30,500.7447927704425,1419.8999542184863],
    ['ɑ','gʊfɑŋɑ',0.104393,114.10,656.9639738790062,1261.0501295780969],
    ['ɑ','gʊfɑŋɑ',0.082586,115.40,690.0448058137032,1419.7442499962647],
  ],
  columns=cols
)
df3
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 ʊ gʊfɑŋɑ 0.066951 102.3 500.744793 1419.899954
1 ɑ gʊfɑŋɑ 0.104393 114.1 656.963974 1261.050130
2 ɑ gʊfɑŋɑ 0.082586 115.4 690.044806 1419.744250

[ŋ̩wɑnɑ]#

df4 = pd.DataFrame(
  data=[
    ['ŋ̩','ŋ̩wɑnɑ',0.109944,103.60,385.7128256347075,1670.9380122978068],
    ['ɑ','ŋ̩wɑnɑ',0.096705,109.80,691.2607346988126,1349.9162934465471],
    ['ɑ','ŋ̩wɑnɑ',0.071231,102.00,636.6214719076272,1561.746116663688],
  ],
  columns=cols
)
df4
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 ŋ̩ ŋ̩wɑnɑ 0.109944 103.6 385.712826 1670.938012
1 ɑ ŋ̩wɑnɑ 0.096705 109.8 691.260735 1349.916293
2 ɑ ŋ̩wɑnɑ 0.071231 102.0 636.621472 1561.746117

[giʤoto]#

df5 = pd.DataFrame(
  data=[
    ['i','giʤoto',0.129482,134.70,342.0308099761518,2008.6442292576407],
    ['o','giʤoto',0.105140,141.00,369.4878212931457,1416.8457811554285],
    ['o','giʤoto',0.130837,164.30,365.7859352775467,1126.0169349503485],
  ],
  columns=cols
)
df5
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 i giʤoto 0.129482 134.7 342.030810 2008.644229
1 o giʤoto 0.105140 141.0 369.487821 1416.845781
2 o giʤoto 0.130837 164.3 365.785935 1126.016935

Data#

Tokens#

df=pd.concat([df1,df2,df3,df4,df5],ignore_index=True)
df
vowel word duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
0 ɪ ɪŋʊɾʊ 0.086119 93.59 466.690302 1766.545145
1 ʊ ɪŋʊɾʊ 0.097062 98.88 515.248472 873.168325
2 ʊ ɪŋʊɾʊ 0.044060 100.40 555.185617 1397.695151
3 ɪ gɪtɑnɪ 0.089908 91.83 364.515698 2023.891020
4 ɑ gɪtɑnɪ 0.105583 100.10 688.618371 1492.431910
5 ɪ gɪtɑnɪ 0.054948 103.30 479.366160 1835.677800
6 ʊ gʊfɑŋɑ 0.066951 102.30 500.744793 1419.899954
7 ɑ gʊfɑŋɑ 0.104393 114.10 656.963974 1261.050130
8 ɑ gʊfɑŋɑ 0.082586 115.40 690.044806 1419.744250
9 ŋ̩ ŋ̩wɑnɑ 0.109944 103.60 385.712826 1670.938012
10 ɑ ŋ̩wɑnɑ 0.096705 109.80 691.260735 1349.916293
11 ɑ ŋ̩wɑnɑ 0.071231 102.00 636.621472 1561.746117
12 i giʤoto 0.129482 134.70 342.030810 2008.644229
13 o giʤoto 0.105140 141.00 369.487821 1416.845781
14 o giʤoto 0.130837 164.30 365.785935 1126.016935

Averages#

df.drop(columns=['word']).groupby(by=['vowel']).mean().rename(columns={'duration_[s]':'avg_duration_[s]'})
avg_duration_[s] avg_pitch_[Hz] avg_f1_[Hz] avg_f2_[Hz]
vowel
i 0.129482 134.700000 342.030810 2008.644229
o 0.117988 152.650000 367.636878 1271.431358
ŋ̩ 0.109944 103.600000 385.712826 1670.938012
ɑ 0.092100 108.280000 672.701872 1416.977740
ɪ 0.076992 96.240000 436.857387 1875.371321
ʊ 0.069358 100.526667 523.726294 1230.254477

Figures#

  • [W] Heine, Bernd (1939-)

  • [W] Morton, Deborah

  • [W] Westermann, Diedric (1875-1956)

Terms#

  • [W] Akan

  • [W] Anii (Basila)

  • [W] Atlantic-Congo Languages

  • [W] Central Tano Languages

  • [W] Ewe

  • [W] Ghana

  • [W] Ghana-Togo Mountain Languages

  • [W] Kwa Languages

  • [W] Mande Languages

  • [W] Niger-Congo Languages

  • [W] Togo

  • [W] Twi

Contents