A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

ᝲ୫A Functional Load Quantification of the Vowel
Systems of Four Asian Englishes

Leah GILNER

ᛵ ஖
本研究は，㧠つのアジア英語，すなわち，香港英語，インド英語，フィリピン英語，およびシンガポール英語における母音体系を機能的負荷の点から分析し，その結果を考察する。機能的負荷（FL）の枠組みを用いることで，コーパスにおける生起頻度の点から言語的特徴を量的に明らかにすることができる。つまり FL により，言語の構造面の記述に言語の運用面に関する記述を加えることができる。本論文では，㧠つのアジア英語の各母音体系を International Corpus of English の ICE-HK, ICE-IND, ICE-PHI,and ICE-SIN から得た生起頻度に基づき，明らかにする。最後に，体系的に一般的な傾向について論じる。

キーワード：機能的負荷，母音体系，諸英語，言語類型論，音声処理

Keywords: functional load, vowel systems, world Englishes,
linguistic typology, speech processing

1. Introduction
The investigation reported in this paper adopts a corpus-based approach to
the description of phonological systems by means of functional load (FL) analyses.
Specifically, FL rankings are provided for the vowel systems of Hong Kong English

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No. 45(HKE), Indian English (IndE), Philippine English (PhilE), and Singapore (SingE) basedon usage data obtained the spoken component of the International Corpus of English
subcorpora (ICE; https://www.ice-corpora.uzh.ch/en.html).
FL has been proposed as a parameter by which to assess the relative amount ofwork carried out by each element of a linguistic class (Hockett, 1955; King, 1967a;
Mathesius, 1929). It has been used extensively in phonology, in particular, and has beenshown to be an informative means by which to observe “…how much a language relieson phonological constructs” (Surendran & Niyogi, 2006, p. 11) as well as the nature anddynamics of the systemic relationships they form (Oh et al., 2015, p. 155). This paper
focuses on vowels systems and provides FL data that is otherwise unavailable in theliterature.
Interest in and applications of FL, originally proposed by Prague School scholars,
have recently re-emerged as the relevance of usage frequency in speech processing
and cognition has been demonstrated by work undertaken in psycholinguistics, corpus
linguistics, and cognitive linguistics (see Brysbaert et al., 2018; Divjak & CaldwellHarris, 2015 for psycholinguistic and cognitive linguistic reviews respectively). FL
complements structural descriptions of phonological systems because it makes it possible
to quantify certain aspects of usage by means of corpus-based observed frequencies,
probabilities of reoccurrence, and other more sophisticated measures derived from these
metrics (e.g., entropy). This method of analysis has, over time, contributed additional
data and insights that has furthered understanding of issues of intelligibility (Munro &Derwing, 2006; Sewell, 2017) as well as cognition and mental representations (Kang,
2012, 2015; Oh et al., 2015; Warren, 2001; Wedel, 2012; Wedel et al., 2013).
Accumulated findings from diverse domains indicate that speech processing involves
multiple cues beyond the obvious auditory input and includes visual, physiological, as
well as additional linguistic information (Huettig et al., 2011; McGurk & Macdonald,
1976; Scarbel et al., 2014). Furthermore, recent developments in neuroscience haveevidenced neural correlates of motor activity directly related to speech perception andproduction (Devlin & Aydelott, 2009). This latest data has renewed interested in gesturebased theories of speech processing such as Motor Theory proposed by Liberman (1985)
and Articulatory Phonology proposed by Browman and Goldstein (1992). The current
investigation contributes to this ongoing discussion, by providing an interpretation of
results in terms of vowel quadrant activation and the corresponding anatomical actors

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A Functional Load Quantification of the Vowel Systems of Four Asian Englishes(e.g., tongue, lips, jaw) and actions (e.g., tongue protraction/protrusion, lip rounding, jaw
lowering) underlying speech production.

2. BackgroundTraditionally, FL has been associated with phonemic systems (Hockett, 1966; King,
1967a; Trubetzkoy, 1939). As King (1967b, p. 831) explains:“The term functional load is customarily used in linguistics to describe the extent
and degree of contrast between linguistic units, usually phonemes…In its simplest
expression, FL is a measure of the number of minimal pairs which can be foundfor a given opposition [Phoneme Pairings (PP), LG]. More generally, in phonology,
it is a measure of the work which two phonemes (or a distinctive feature) do in
keeping utterances apart - in other words, a gauge of the frequency with which twophonemes contrast in all possible environments.”
It is important to note that the prevalent contemporary approach to the study of FL
adopts an information-theoretic perspective based on the notion of entropy, a constructborrowed from information theory (Shannon & Weaver, 1949). In the context of FL
studies, entropy is used to refer to the amount of information lost by a linguistic class when
two of its constituent elements merge or coalesce. The earliest formulation of these kindsof entropy measures was done by Hockett (1966). Fundamental to Hockett’s method is theidea that the absence of an element leads to a redistribution of work across the remaining
elements. From this perspective, phoneme pairings are not independent. “They cannot
be deleted; they can only coalesce” (Hockett, 1966: 10). This initial formulation has
been further elaborated within information-theoretic frameworks. Surendran and Niyogi(2003, 2006) demonstrated its usefulness in examining phonological classes larger thanphonemes and phonemic contrasts such as vowels, consonants, tone, and stress. Entropybased FL analyses have been conducted on several large languages including Cantonese,
Mandarin, English, French, German, Italian, Japanese, Korean, and Swahili (Oh et al.,2015). In the case of English, researchers have relied on the CELEX lexical databasewhich contains phonological forms based on a British Received Pronunciation (BRP)
phonological model and corpus frequencies from the COBUILD corpus (Burnage, 1990).

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No. 45Scholarly interest in phonological systems of varieties of world Englishes has
produced a rather large body of literature in a relatively short period of time. Since
the 1980s, the focus has been on expanding the pool of resources available on British
and U.S. varieties and dialects with comparable descriptions of the varieties spoken in
postcolonial regions (Hughes et al., 2012; Kortmann & Schneider, 2004; Wells, 1982).
It is thanks to strong structural traditions that we have been able to accumulate parallelsystemic descriptions of the phonemic inventories of English found in locales acrossthe continents. Some specialists see this type of research as fundamental to “English asa World Language” studies (Mair, 2005). Perhaps the most current and comprehensive
work to date is the Handbook of Varieties of English (HVE) edited by Kortmann &Schneider (2004). The volume includes descriptions that follow a common template andthus provide a framework for not only inspection of individual varieties but a platform
for speculation based on the aggregation of insights associated with regional ecologies
and historical trajectories. The treatments provided in HVE have made it possible toobserve patterns based on the survey of features across a great number of varieties andto propose both regional and global tendencies (Kortmann & Schneider, 2004). The
accumulation of datasets has thus allowed for broader and more robust observations
regarding distributional characteristics of the English sound system, in its multiple
manifestations. These efforts are acknowledged to be “a magnificent testimony to theamount of research which has been carried out in the last quarter century on variation in
English around the world” (Britain, 2007, p. 746).
This paper focuses on vowels because they are of particular interest due to theirmultifunctionality. Briefly, vowels play a role in speech processing because of theirrelative perceptual prominence which helps listeners parse the speech stream (Bonatti
et al., 2005). The human speech processing mechanism appears to be attuned to thesonority peaks that vowels contribute to the acoustic signal, exploiting this cue in order to
identify words and grammatical structures in a continuous stream of sounds (Bonatti etal., 2005; Fogerty & Kewley-Port, 2009; Stilp & Kluender, 2010). Moreover, vowels havebeen found to be largely responsible for the rhythmic qualities of speech. The musicalityof speech is determined by alternations in prominence among phonological units (Ramus
et al., 1999). Vowels carry prosodic cues such as stress and tone that constitute melody
and are associated with indexical and emotional cues (Nespor et al., 2002). It can thus besaid that vowels carry the lilt and cadence of speakers’ phonological signatures and thus

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A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

convey this aspect of identity.
The investigation makes use of four parallel corpora from the International Corpus
of English (hereafter ICE; https://www.ice-corpora.uzh.ch/en.html). The availability ofthese data sources makes it possible to produce analogous descriptions that reflect
localized and situated use of the English language as it manifests itself uniquely in
different society. The four varieties under investigation represent locales particular in
their historical, social, political, and economic profiles. The role of the English language
within each milieu is similarly particular, acquiring additional differentiation as eachsociety follows its own evolutionary trajectory (Schneider, 2003). Furthermore, various
languages cohabitate in these environments and, naturally, multiple registers coexist inthem as well. In this manner, the linguistic habitus of the members of each communityof speakers reflects an intricate and idiosyncratic interplay of a wide array of linguistic,social, interactive, and cognitive factors (Blommaert & Backus, 2012; Busch, 2012;
Canagarajah, 2018; Hruschka et al., 2009; Mufwene & Vigouroux, 2017; Van Rooy,2010; Wei, 2011). Results may thus shed light on systemic relationships formed among
phonological categories and be used in future research concerning how communicative
experiences shape multilingual linguistic repertoires (Bybee, 2006; Mauranen, 2018;
Pierrehumbert, 2012; Wedel, 2007).

3. Methodology
3.1. Data
The spoken components of ICE-HK, ICE-IND, ICE-PHI, and ICE-SIN wereanalyzed in order to elicit their corresponding dominant vocabularies (DOVO) following
the methodology described in Gilner and Morales (2020). The size of the corpora andthe number of phonemically transcribed wordforms analyzed for each one are shown in
Table 1. Description of corpora and data sets
Corpus size

Transcribed wordforms

Coverage

ICE-HK

919,082

811,308

88.27%

ICE-IND

667,116

570,456

85.51%

ICE-PHI653,075

563,18386.24%ICE-SIN

661,728

580,664

87.75%

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Table 1. Coverage values indicate the percent of all the running words in each corpus thatwere transcribed.
As is established practice in FL studies, phonological representations of citation
forms were used for the analyses undertaken by this investigation.1 Transcriptions were
produced based on the phoneme inventories and lexical sets provided by Hung (2000) for
HKE, Gargesh (2004) for IndE, Tayao (2004) for PhilE, and Low (2016) for SingE. These
descriptions are widely accessible, comprehensive, and correspond to the pronunciation
models adopted by the Oxford English Dictionary2. Inter-rater and intra-rater reliability
checks of phonemic transcriptions were conducted, yielding an average of 95.86%
agreement.

3.2. Functional load calculations
As Oh et al. (2015) explain, the information-theoretic approach to FL analysis views
language L as a source of sequences made up of word-forms w taken from of a finite setof size NL.
Equation 1 shows the entropy H of language L calculated over its lexicon.
ேಽሺሻ ൌ െ ෍ ‫݌‬௪೔ ‫ כ‬ଶሺ‫݌‬௪೔ ሻ௜ୀଵEquation 1. Amount of information or entropy in language L

Equation 1 calculates the probability of word-forms (pwi) as a factor of the frequencyof occurrence of a word in a corpus. The entropy measure H(L) is used to represent theinitial state of the system (Shannon, 1948).
‫ܮܨ‬஦ǡந ൌ‫ܪ‬ሺ‫ܮ‬ሻȂ ‫ܪ‬ሺ‫כܮ‬ఝట ሻ‫ܪ‬ሺ‫ܮ‬ሻEquation 2. Functional load of the contrast between two phonemes φ and ψ

Equation 2 shows the FL of a contrast between two phonemes φ and ψ. FL φ, ψ isdefined as the relative difference in the entropies between two system H(L) and H(L*φψ),often normalized as shown in Equation 2 (Surendran & Niyogi, 2003). Note that H(L*φψ)is calculated by coalescing the frequencies of all the mergers involving the phonemes φ

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A Functional Load Quantification of the Vowel Systems of Four Asian Englishesand ψ.
ͳ‫ܮܨ‬Ԣ஦ ൌ ෍ ‫ܮܨ‬஦ǡநʹటEquation 3. Functional load of a phoneme φAgain following Oh et al. (2015), it is possible to estimate the FL of a phoneme byadding all the mergers it participates in (as shown in Equation 3) with the normalization
factor ½ to ensure that the FL of mergers are not counted twice since φ, ψ = ψ, φ.

3.3. Complementary measures
Where useful, the discussion of results also includes the following two measures:
dominant relative normalization (DRN) and least-dominant relative normalization(LDRN). The first measure, DRN, is found in various forms in the literature (Brown,
1988; Catford, 1987; Gilner & Morales, 2010; Herdan, 1958) and expresses the FL of eachmember as a fraction of the member with the highest FL. The second measure, LDRN,
expresses the FL of each member as a magnitude of the member with the lowest FL.
DRN and LDRN express equivalent ratios that provide a means by which to assess themeasures in relation to each other rather than as a fraction of the whole.
a) ‫ܴܰܦ‬ఝ ൌ

௑ക

௅஽ோே

ൌ ௅஽ோேക

௑ಾ
௑ക

ಾ

஽ோே

b) ‫ܴܰܦܮ‬ఝ ൌ ௑ ൌ ஽ோேക೘೘Equation 4. Equivalent relationships between DRN and LDRNAs shown by Equation 4 a and b, given a set S of values X, the DRN and LDRN of
an element φ all express equivalent ratios, each relative to a different measure, namely,
the largest value (XM), and the smallest value (Xm), respectively.
This supplementary manner of presentation expresses proportional relationships
relative to a given member. This approach is particularly suitable for FL analyses whichseek to quantify the relative amount of work done by members of class and thereby reveal
the systemic synergy of usage-driven patterns of organization (Pellegrino et al., 2009).
DRN and LDRN measures contribute to the construction of a referential framework fordescribing the system and its dynamic behavior, what Pellegrino et al. (2009) refer to as

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No. 45the macroscopic level of complex patterns.

4. Results and discussion
4.1. Usage-driven description of the HKE vowel system
The results for the model of the HKE vowel system (Hung, 2000) reveal a markedly
uneven distribution of work across the 15 members, as shown in Chart 1 below. Each
phoneme is plotted along the horizontal axis in descending order of the relative FL thatis plotted along the vertical axis. It can be seen that the phoneme /i/ obtained the greatest
FL, the phoneme /eɪ/ obtained the 2nd greatest FL, the phoneme /ɑ/ the 3rd greatest and soon. A steep downward slope is established by the plotted points that correspond to thesethree top ranked members. A leveling off in the FL of the phonemes /u/ and /aɪ/ ranked 4th
and 5th is observed. Another steep downward slope is created by the FL corresponding to
the next two phonemes /ɛ/ and /ɔ/. From there on, FL values continue to decline in smaller
and more regular increments.

i

e

ɑ

u

a

ɛ

ɔ

ɛə oʊ

ʌ

aʊ

ɜ

ɪə ʊə ɔɪChart 1. HKE FL distribution curve

Table 2 presents the actual FL values, which range from a maximum of 0.0242 toa minimum of 0.0003. As explained in the Methodology section, DRN values make itpossible to describe FL values in terms of fractions of the member with the highest FL.
In this manner, it can be seen that the 2nd ranked member carries out 66.61% of the work
the 1st ranked member does. The 3rd, 4th, and 5th ranked members make lesser but rather
similar contributions, each carrying out approximately half of the amount of work thatthe 1st ranked member does.

8A Functional Load Quantification of the Vowel Systems of Four Asian Englishes
Table 2. FL ranking of the vowel inventory of HKE
Rank

Segment
1

i

2
3

FL

DRN

LDRN

0.0242

100%

85.55

eɪ

0.016166.61%

56.98

ɑ0.012551.45%

44.02

4

u

0.012451.18%

43.79

5

aɪ

0.012250.46%

43.17

6

ɛ

0.009438.85%

33.23

7

ɔ

0.006225.46%

21.79

8

ɛə

0.005824.09%

20.61

9

oʊ

0.0051

20.91%

17.89

10

ʌ

0.005020.57%

17.60

11

aʊ

0.0041

16.91%

14.46

12

ɜ

0.003715.42%

13.19

13

ɪə

0.003012.48%

10.68

14

ʊə

0.0022

8.98%

7.68

15

ɔɪ

0.0003

1.17%

1.00

Recall that LDRN values express FL in terms of magnitudes relative to the member
with the lowest FL. In this manner, it is possible to easily see that the 1st ranked member
does 85.55 times the amount of work than the lowest-ranked member; the 2nd ranked
member 56.89 times more; the 3rd ranked member 44.02 times more and the 4th and 5th
ranked members approximately 43 times more work than the lowest-ranked one.
These values expose a tendency toward close articulations. Among the anteriorbased phonemes, the most close phoneme /i/ does 2.5 times the amount of work as theleast close member /ɛ/; the intermediate member /eɪ/ does a bit less than twice the work
the least close counterpart. Among the posterior-based phonemes, however, there is very
little difference between the FL values obtained by the most open member /ɑ/ and mostclose member /u/.
Figure 1 provides a visual display of these usage-driven trends. The members of
HKE phonemic inventory that obtained DRN values >= 1% as presented in Table 2 areindicated by circles. The circle around each member is proportional to its relative amountwork so that the phoneme /i/ (DRN=100%) is the largest, the circle surrounding thephoneme /eɪ/ is approximately 67% the size of the largest one (DRN=66.61%), and so on.

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No. 45Figure 1. Vowel quadrant activation of HKE

This visualization shows that anterior-based articulations are relatively most active.
The high, front, tense /i/ contributes most to the work carried out by this system. The roleof anterior-based articulations is further reinforced by the occupant of the next positionin this ranking, the diphthong /eɪ/. Further scrutiny reveals that the seven members which
populate the frontal region of the vowel space (including initial and terminal targets ofdiphthongs) collaborate to undertake 58.1% of the total amount of work carried out by thissystem. The 1st and 2nd ranked members account for more than half of that portion.

4.2. Usage-driven description of the IndE vowel system
Chart 2 displays results for the 20 members of the phonological model of IndE
(Gargesh, 2004). Again, a markedly uneven distribution of work across the membersof the system is revealed. The phoneme /e:/ is the member with the greatest FL andestablishes the highest point on the curve. A relatively steep downward slope is observed
among the plotted points corresponding to the phonemes which follow ranked 2nd, 3rd, and4th, namely, /ɪ/ - /aɪ/ - /i:/. Relatively short steep downward slopes are seen at two points

e: ɪ a i: æ o: aʊ ə u: ɛ ɔ ɑ: ɔ: ʌ ʊ ɜ: ɪə ɔɪ aɪə aChart 2. IndE FL distribution curve10

A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

in the curve: towards the lower-upper end of the ranking between the phonemes /æ/ and/o:/ and rather farther down toward the lower end of the ranking between the phonemes/ʌ/ and /ʊ/. The middle of the curve is characterized by clusters of members with similar
FL values (indicated by fairly parallel lines) interspersed with incremental drops while
the tail end shows relatively steady and small declines in FL.
Table 3 presents the raw FL measures along with DRN and LDRN values. FL ranges
from a maximum of 0.0092 to a minimum of 0.0001. The 20th ranked member, /a/, does
not establish contrastive relationships with any other members and, consequently, its
FL is 0 since its coalescing with any member in the system would not lead to a change
in entropy. The DRN values indicate that the 2nd ranked member contributes 0.8209, or
82.09%, the amount of work that the 1st ranked one does; the 3rd ranked member 0.7030,

Table 3. FL ranking of the vowel inventory of IndE
Rank

Segment

FL

DRN

LDRN

1

e:

0.0092

100%

98.43

2

ɪ

0.007682.09%

80.80

3

aɪ

0.006570.30%

69.20

4

i:

0.005963.97%

62.97

5

æ

0.005963.57%

62.57

6

o:

0.004447.32%

46.58

7

aʊ

0.004346.87%

46.13

8

ə

0.003639.35%

38.73

9

u:

0.003638.95%

38.34

10

ɛ

0.003638.85%

38.24

11

ɔ

0.003032.10%

31.60

12

ɑ:

0.002931.69%

31.19

13

ɔ:

0.002223.78%

23.41

14

ʌ

0.002223.65%

23.28

15

ʊ

0.0006

6.33%

6.23

16

ɜ:

0.0006

6.02%

5.92

17

ɪə

0.0005

5.31%

5.22

18

ɔɪ

0.0003

2.83%

2.79

19

aɪə

0.0001

1.02%

1.00

20

a

0

-

-

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No. 45or 70.30%; the 4th and 5th ranked members average 63.77% of the contribution that the 1st
ranked member does.
The LRDN values show that the 1st ranked member carries out 98.43 times theamount of work as the member ranked 19th, the 2nd ranked member 80.80 times theamount, the 3rd ranked member 69.20 times and the 4th and 5th ranked members average
62.52 times the amount of work as the member ranked 19th. As observed in Chart 2, a
noticeable cluster is formed by the members ranked 8th, 9th, and 10th, which each workroughly 38 times more than the member ranked 19th. The phonemes ranked 6th and 7th
carry out roughly 46 times the amount of work of the member with the lowest FL.
Figure 2 provides a visual representation of these usage distributions. As was the casewith HKE, the members with DRN values between 100% and 1% are represented withproportionally sized circles. The relative importance of the two top-ranked phonemes
identifies the intermediate and upper zones of the anterior region of the vowel space as
relatively most active. The anterior region of articulation is also activated by the threephonemes that follow in this ranking. The relevance of anterior articulations is reinforcedby the phonemes /i:/ and /æ/, which are both articulated in the frontal areas of the oralcavity. The former targets the extreme upper and the latter the extreme lower perimeter
defined by this vowel system. The most energetic intermediate member /o:/ is the greatest
contributor among the posterior-based members. This phoneme does 7 times the amountof work as the lowest ranking posterior-based counterpart /ʊ/. The most close member inthis system /u:/ works 6 times as much as its quadrant co-occupant.

Figure 2. Vowel quadrant activation of IndE

Among the two monophthongs that co-occupy the high-anterior region, the lessenergetic member is more active. The opposite is true for the co-occupants of the12

A Functional Load Quantification of the Vowel Systems of Four Asian Englishesintermediate-anterior region. The more energetic member tops the ranking while its
lax counterpart is ranked 10th. Among the posterior-based members, the more energetic
member of the intermediate region is the most active, ranked 6th; its co-occupants areranked 11th, 13th, and 14th. The more energetic co-occupant of the upper-posterior region
also obtains higher FL values than its lax counterpart. These members are ranked 9th and15th, respectively.

4.3. Usage-driven description of the PhilE vowel system
Chart 3 displays the results for the 13 members of the of the PhilE model (Tayao,
2004) in the form of the FL distribution curve. A markedly uneven distribution of work
across the members of this system is observed, as was the case in the previous varieties.
The phoneme /i:/ obtains the greatest functional load and hence establishes the highest
point of the curve. The plotted points of the following four members, namely, /ɑ, o, eɪ,ɑɪ/ form the relatively steepest slope of the curve. Noticeable dips in the curve are seen
between the members /ɑɪ/ and /ɑʊ/, ranked 5th and 6th, and between the members /ʌ/and /e/, ranked 9th and 10th. The slight downward slope seen in the middle of the curve
indicates relatively small decreases in FL of the members /ɑʊ, u:, ɛ, ʌ/ and the relatively
flat end of the curve indicative of rather similar FL among the members /e, ɪ, i, oɪ/.

i:

ɑ

o

e

ɑɪ

ɑʊ

u:

ɛ

ʌ

e

ɪ

i

oɪ

Chart 3. PhilE FL distribution curve

Table 4 presents the actual FL values in rank order for PhilE. The values range froma maximum of 0.0147 to a minimum of 0.0003. The DRN values instantiate the fairly
steady decrease in relative contributions throughout the ranking, as observed in Chart 3.
The 2nd ranked member contributes 0.8738, or 87.38%, of the amount of information that

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No. 45the 1st ranked one does; the 3rd ranked member 0.7424, or 74.24%; the 4th ranked member
63.66% and the 5th ranked member 55.5% of the information that the 1st ranked member
does. The top two members demarcate the upper anterior and lower posterior regions of
the vowel space. The next two members delineate the intermediate zone of articulationand demarcate the anterior from the posterior regions.
Table 4. FL ranking of the vowel inventory of the PhilE
Rank

Segment

FL

DRN

LDRN

1

i:

0.0147

100%

48.76

2

ɑ

0.012987.76%

42.61

3

o

0.010974.15%

36.20

4

eɪ

0.009463.95%

31.04

5

ɑɪ

0.008255.78%

27.06

6

ɑʊ

0.005134.69%

16.86

7

u:

0.004731.97%

15.73

8

ɛ

0.004329.25%

14.36

9

ʌ

0.004027.21%

13.10

10

e

0.0008

5.44%

2.74

11

ɪ

0.0007

4.76%

2.46

12

i

0.0007

4.76%

2.36

13

oɪ

0.0003

2.04%

1.00

The LRDN values make evident certain differences in magnitudes of relative
contribution. The 1st ranked member /i:/, for instance, carries out 21 times the amountof work as its quadrant co-occupants ranked 11th and 12th. This upper-anterior-based

Figure 3. Vowel quadrant activation of PhilE

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A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

member also makes a noticeably larger contribution than its intermediate-anterior-based
counterparts, ranked 4th, 8th, and 10th; 18 times greater than that of the phoneme /e/, 5times greater than that of the phoneme /ɛ/, and 11 times greater than that of the phoneme/eɪ/. The differences in magnitude of contribution is not as great among the posteriorbased members. The highest-ranking posterior-based phoneme /ɑ/ contributes 3.23 times
the amount of its lowest ranked counterpart /ʌ/ and 2.73 times the amount of its closest
ranked member /o/.
Figure 3 shows how the more active members are rather widely dispersed throughout
the vowel space. The first two members occupy diametrically opposed quadrants, theupper-anterior and the lower-posterior. The 3rd ranked member occupies the intermediatezone of the posterior region and the 4th ranked member the intermediate-anterior.
Articulation of the diphthong ranked 5th involves movement from lower-posterior toupper-anterior while the diphthong ranked 6th involves movement from lower-posterior
to upper-posterior. Three of the members at the bottom of the ranking are anterior-based
phonemes that co-occupy the vowel quadrant with a more active member.

4.4. Usage-driven description of the SingE vowel system
Chart 4 displays the curve of distribution of FL values for the 17 members of
SingE (Low, 2016). As has come to be expected, the results reveal a markedly uneven
distribution of work across the members. The phoneme /i/ obtains the greatest functionalload and hence establishes the highest point of the curve. The plotted points of thefollowing four members, namely, /e: - aɪ - ɛ - ɜ:/ form the relatively steepest slope of thecurve. A leveling off in the curve is seen across the next few members in the ranking,

i

e: a

ɛ

ɜ: u: ɔ: ɑ: o: ɛə aʊ ɒ iəi ʊə ʌ

Chart 4. Curve of FL distribution of SingE

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namely, /u: - ɔ: - ɑ:/. The latter half of the curve shows a relatively steady decline in FL
values.
Table 5 presents the actual FL measures as well as DRN and LDRN values for
SingE. DRN values indicate that that the 2nd ranked member does approximately 68.94%
of the work that the 1st ranked member does. The 3rd ranked member makes 56.02% of
the contribution of the 1st ranked member and the 4th ranked member 39.13%. Several
posterior-based members cluster together in the middle of the ranking. The highest
ranked posterior-based member does 30.35% of the work of the highest ranked anteriorbased counterpart and is ranked 6th. This member occupies the upper zone of the vowel
space. Its co-occupant is ranked 11th. The next largest contributor among the posteriorbased members occupies the intermediate zone and is ranked 7th. It does a rather similar
amount of work as the 6th ranked member. Its quadrant co-occupants are ranked 9th
and 15th. A more open articulation among the posterior-based members, ranked 8th,
contributes 28.75% of that of the 1st ranked member. Its quadrant co-occupant is ranked
Table 5. FL ranking of the vowel inventory of the SingE
Rank

Segment

FL

DRN

LDRN

1

i

0.0209100%

106.122e:0.014468.90%

73.16

3

aɪ

0.011755.98%

59.45

4

ɛ

0.008239.23%

41.52

5

ɜ:

0.006732.06%

34.00

6

u:

0.006430.62%

32.21

7

ɔ:

0.006229.67%

31.59

8

ɑ:

0.006028.71%

30.51

9

o:

0.005224.88%

26.14

10

ɛə

0.005023.92%

25.44

11

aʊ

0.0041

19.62%

20.88

12

ɒ

0.003215.31%

16.26

13

iə

0.002813.40%

14.32

14

ʊə

0.002411.48%

11.93

15

ʌ

0.002110.05%

10.58

16

ʊ

0.0015

7.18%

7.56

17

ɔɪ

0.0002

0.96%

1.00

16

A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

12th and does about half the amount of work of its higher ranked counterpart.
Speaking in terms of magnitudes of contribution, LDRN values indicate thedisparity among members of this vowel system. The 1st ranked member does more than
100 times the amount of work that the 17th ranked member does. The 3rd ranked member
does almost 60 times the work that the lowest ranked member does. Nine out of the 17
members have LDRN values that are less than the average (=31.92). Among the anteriorbased monophthongs, the LDRN of highest ranked member /i/ is 2.5 times greater thanthat of its lowest ranked counterpart /ɛ/. A wider range is observed among the posteriorbased members. The LDRN values of the members ranked 6th, 7th, and 8th are roughly 4times greater than that of the lowest ranked posterior-based member /ʊ/. The phoneme /ʌ/adjacent to this one, ranked 15th, obtains an LDRN that is 1.4 times larger.

Figure 4. Vowel quadrant activation of SingE

Figure 4 shows how FL values correspond to vowel quadrant activation. The ranking
reveals systemic articulatory patterns associated with raised and protracted tongue
movements. Four of the top five members are anterior-based articulations, including theanterior-closing diphthong. Two of these members are co-occupants of the intermediateanterior quadrant of the vowel space. The cluster of phonemes ranked 5th to 9th are all nonanterior-based lengthened articulations. The phoneme /ɜ:/ further reinforces the relevanceof articulations produced in the intermediate zone and, at the same time, indicates therole of tongue retraction in articulating distinctive constituents. The phonemes /u: - ɔ:- ɑ:/ establish the relevance of posterior-based articulations in distinguishing membersof this system. These three phonemes span the height of the vowel space, distributing
activation similarly across the upper, intermediate, and lower zones.

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5. General observations
This paper has presented results obtained from FL analyses of the vowel systems
of four varieties of English. Findings demonstrate how this methodology can be applied
to the domain of descriptive studies in order to provide a usage-driven quantitative
perspective. Each of the four systems investigated displayed distinct patterns of uneven
distributions and revealed systemic relationships among members in terms of relative
operationality (Pellegrino et al., 2011). These findings thus provide additional data thatserves to document the large diversity that is present among and within phonologicalsystems.
From the perspective of articulatory features, these tendencies can be considered interms of the front/back and open/close articulatory dimensions, operationalized as [front– central – back] and [high – mid – low], respectively. Chart 5 presents results of the FLof these articulatory features. In terms of the open/close dimension, the feature [mid] iscomparably active in each of the four varieties. This feature is relatively most active in
the SingE and IndE while slightly less so in HKE and PhilE systems. Generally speaking,the feature [high] does slightly more work than the feature [mid] in the HKE and PhilE
systems while the tendency is reversed for the IndE and SingE systems. The feature [low]consistently obtains the lowest FL values across these systems.

HKE

IndE

PhilE

SingE

100%
95%
90%
85%
80%
75%
70%
65%
60%
55%
50%
high

mid

low

front

centralChart 5. FL of articulatory features across varieties

18

back

A Functional Load Quantification of the Vowel Systems of Four Asian Englishes

Regarding the front/back dimension, the feature [front] makes comparably larger
contributions to each of the four systems. The feature [back] obtains similar FL values
as the feature [front] in PhilE and SingE and noticeably lesser FL in HKE and IndE.
The feature [central] is noticeably less of a contributor across systems. This feature isrelatively most active in the IndE system and not used at all in PhilE and SingE.

6. Conclusion
This summary review of findings encapsulates how the FL values have beenused to quantify the usage of the phonemes that constitute each vowel system. Several
venues of potential application for this usage-driven data present themselves. When it
comes to contemporary English studies, documentation and description are of particular
relevance. The large body of referential work available on the language has traditionallybeen based on a limited and limiting perception of its users, uses, and usage. The
aggregation of descriptive data sets can help advance the field in efforts to characterize
the contemporary reality of the English language in its various forms and functions.
Referential works such as HVE which provide structural descriptions of phonologicaland grammatical features, encourage typological analyses and, as a consequence, afford
a basis for more informed theorization regarding similarities and differences as well as
speculating about the role of experience in cognitive categorization. Findings presented
here add to the resource pool available to researchers interested in pursuing such topics.
These findings are also relevant to substance-based theories of speech communication
which position patterning of speech sounds in human languages as crucial to understanding
productive/perceptual mechanisms underlying speaker-listener interactions (Liljencrants& Lindblom, 1972; Schwartz et al., 1997; Stevens, 2002). Usage-based phonology, forexample, considers exposure and experience with situated and embodied meaning
fundamental to understanding mental representations of phonological systems. A
central concern is understanding and explaining how phonological categories are formed
from highly variable speech tokens (Silverman, 2013). Contextual, physiological, andpsychological factors conspire to produce “dramatic” acoustic invariance (Taylor, 2009,p. 23) that makes understanding how verbal communication succeeds “a major challenge”(Pitt, 2009, p. 19). Accumulated evidence demonstrates that a usage-based framework
accommodates the invariance problem by allowing mental representations of phonological

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No. 45targets and patterns to gradually build up over time and with experience (Bybee, 1994;
McQueen et al., 2006, 2006; Norris, 2003; Pierrehumbert, 2001; Wedel, 2012). The
FL measures obtained from this investigation provide usage-driven quantification ofhierarchies of phonological categories. These findings might thus be used to pursue
inquiry into usage-based, exemplar-driven speech communication models that propose
cognitive schemata emerge through “the collection of echoes” (Pierrehumbert, 2006, p.
523) retained from usage events.
The world Englishes paradigm has increased the granularity of analysis of localized
communicative practices and the distributed functions bestowed upon co-existinglanguages within particular societies. What we know about the multiple expressions ofEnglish as well as the distinct functions that co-existing languages and their associatedregisters serve in different linguacultural milieus is evolving as research continues toaccumulate. Perspectives offered by Van Rooy (2010), for example, prompt speculation
regarding the interplay between underlying cognitive processes and situational
functionality in the shaping of linguistic varieties. Van Rooy proposes that individuals’
cognitive representations and the conventions of different societies of English users “castnew light on the role of variability in language” (Van Rooy, 2010, p. 16). Van Rooy’s
discussion raises interesting questions regarding the nature of input, its role in impacting
cognitive schemata and, consequently, mediating variability as well as shaping varieties.
Results discussed here encourage speculation regarding processing biases rooted inlinguistic experience based on encountered exemplars, for which behavioral evidence
continues to accumulate (Clopper, 2014; Clopper & Bradlow, 2007, 2009; Cutler et al.,2008; McQueen, 1991; McQueen & Cutler, 2010). Thus, it is tentatively proposed that
FL analyses have something to contribute to discussions regarding language typology(Kortmann & Schneider, 2004; Schwartz et al., 1997, 2015), language dynamics andevolution (Hruschka et al., 2009; Wedel, 2012) as well as inclusive and pluricentric
approaches to the study and teaching of the English language (Canagarajah, 2013, 2018;
Cook, 2017; Kirkpatrick, 2010).
Notes
1

It merits mention that Surendran and Niyogi (2006) demonstrated an 82% correlation between
FL measures obtained from corpora of phonetically-transcribed and phonologically-transcribed
forms.

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A Functional Load Quantification of the Vowel Systems of Four Asian Englishes
2

Confirmed at https://public.oed.com/how-to-use-the-oed/key-to-pronunciation/pronunciationsfor-world-englishes/

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