Vowel and Consonant Contrasts

Vowel and Consonant Contrasts

Leah GILNER

ᛵǽ஖
教師の大切な役割の一つは何を教えるかという選択をすることである。
発音指導に関しては機能的荷重（Functional Load: FL）の潜在的役割が考えられる。英語の発音教材の中で Brown (1988) と Catford (1987) によって作成された母音と子音対立の FL ランキングは長年にわたり高く評価されているものである。本論文はその FL ランキングの歴史と背景さらに作成手法について述べ，筆者の用法基盤アプローチを用いた FL ランキングの記述例を紹介すると同時にこのアプローチがどのような分析を可能にするかを提示したい。
キーワード：母音と子音対立，機能的荷重，英語発音，発音教材，諸英語

Keywords: Phoneme oppositions, functional load, English
pronunciation, pronunciation teaching, world Englishes

1

Introduction
The concept of functional load (FL) has attracted the attention of researchersinterested in pronunciation teaching and learning over the decades. Consequently, it
is relevant to explicitly state what FL refers to as well as to review its interpretations
and applications. FL was initially formalized in the 1930s by the Prague School as:“The degree of utilization of a phonological opposition for distinguishing different

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meanings of words in a given language” (Vachek et al., 2003, p. 82). A reformulation
often cited by pronunciation researchers comes from King (1967, p. 831) who distilled
the concept down to “the extent and degree of contrast between linguistic units, usuallyphonemes”. Of critical importance, King recognized the central role of textual frequency“as well as, or instead of, the mere lexical utilization of phoneme oppositions” whenestimating FL (Catford, 1988, p. 4). The two FL rankings of British RP (hereafter BRP)
phoneme contrasts created by Brown (1988) and Catford (1987) still used today by
applied linguistics researchers are based on this formulation of FL. Brown, for instance,
deferred to King’s conception when devising his ranking and Catford identified using
text frequencies as a preferred method of estimation, although one he was not able topursue.
Both Brown and Catford proposed FL as a means by which to objectively
calculate relative importance and thus identify priorities for efficient implementationof pronunciation training. To this end, they provided the field with FL measures of BRP
phoneme contrasts with which to undertake the task. Munro and Derwing (2006, p. 522)
further stimulated interest in FL among researchers with an exploratory study that used
the Brown and Catford rankings to investigate how useful FL could be as “a means ofpredicting accentedness and comprehensibility ratings”. Subsequently, Kang and Moran(2014, p. 177) used the rankings to assess how phonological errors affect oral assessment
and Suzukida and Saito (2019, p. 6) used them to determine which “segmental features
are crucial for L2 comprehensibility judgments”. Results from each of these studies led
the researchers to conclude that “high FL” contrasts have a statistically significant impact
on listeners’ ratings of comprehensibility while “low FL” errors did not.
Encouraged by findings like these, Munro and Derwing (2015) include the replicationand expansion of FL investigations in their prospectus for pronunciation research in the
21st century. Sewell (2021, p. 5) proposes broader potential applications and presentscogent arguments for the usefulness of FL as an informative heuristic in “assessing
questions of language acquisition and language teaching, and relating them in turn tolanguage usage and language change”. Notably, Sewell also acknowledges the need toreevaluate the “go-to” resources, meaning the lists prepared by Brown and Catford, inlight of modern corpus data and statistical modeling in order to supplement existing FL
measures in ways that reflect contemporary analytical methods as well as globalized andlocalized usage of English.

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Vowel and Consonant Contrasts

This manuscript addresses these concerns as follows. First, it provides a criticalreview of Brown (1988)1 and Catford (1987)2 whose FL rankings are most often used byresearchers. Second, it presents FL rankings for vowel and consonant contrasts obtained
from a modern, usage-based, corpus-driven study intended to replicate work of Brown
and Catford (to the extent possible).

2

Review of referential FL rankings
Researchers today continue to rely on the FL rankings of BRP vowel and consonant

contrasts created by Brown and Catford (Hyeseung Jeong & Bosse Thorén, 2019; Kang
& Moran, 2014; Munro & Derwing, 2006; Suzukida & Saito, 2019). Thus, the first task ofthis manuscript is to elucidate what Brown and Catford did precisely. In particular, proper
understanding implies that the origin of their data must be identified without ambiguity
as must the manner in which this data was analyzed in order to produce their rankings.

2.1

Brown’s work
Brown (1988, p. 593) centers his discussion of FL around the “dilemma” confronted

by teachers as to which features “merit precious class time”. In his survey of the literature,
he reviews proposed interpretations researchers have made when applying FL to the taskof describing linguistic systems and the process of sound change, observing an untapped
potential application to the area of language teaching. Relating to this specific domain,
Brown (1988, p. 596) confines his concerns to BRP phoneme pairs which, according
to him, “are often conflated by learners”3 and enumerates 12 factors to consider when
applying the construct to pronunciation teaching. These factors pertain to aspects at boththe segmental and lexical levels. Regarding segmental aspects, factors encompass the
cumulative frequencies of phoneme pairs and probabilities of occurrence of individualphonemes, phonotactic constraints along with acoustic and articulatory similarity. At
the lexical level, considerations include lexical frequency, the number and frequency ofminimal pairs (MPs) associated with a given contrast along with grammatical function
and context of use of members of MPs.
After touching upon each of these factors in turn, Brown (1988, p. 603) concludes that“cumulative frequency and the abundance of MPs would seem to be the most important”
and proposes “a rank ordering of [B]RP phonemes often conflated by learners”. The

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rank is arranged in two 10-point scales, one for vowels and one for consonants, with 10
representing the pairs of greatest priority. However, Brown does not explain the origin of
the data or the methodology he employed.
It is within reason to presume that the frequency data comes from Denes (1964)4,
whose work Brown referred to when reporting cumulative frequencies for somephonemes. Yet, attempts made to reconstruct Brown’s ranking from Denes’ data fail. For
example, multiple phoneme pairs are clustered at some ranks, giving the impression thatsome pairs, for example /e, æ/ and /æ, ʌ/, have equal cumulative frequencies and the same
number of MPs. This is not the case5.

2.2

Catford’s work
Catford (1987, p. 88) describes frequency and FL as two principles that can be used

to make “a deliberate selection of items to be taught”. Frequency, he explains, “is thenumber of times that a phoneme or phonemic opposition occurs per thousand wordsof text”. However, he fervently explains his inability to conduct any sort of frequency
analysis, abandoning this approach in favor of a type-based one. He explicitly cautions
that textual frequency was not taken into account in any way to create his rankings.
Summing up, in Catford’s own words:“No doubt, it would have been better to do the count in a more complete and reliableway (nowadays using a computer) than going systematically through one’s own
inventory of phonological word forms. It was because I assumed for a very long timethat someone else would do, or had done, a better job, that my data remained so longunpublished! So far as I know, however, nobody has done so up to now. I wish theywould!” (Catford, 1988, p. 19)
Catford’s adoption of a type-based approach means that his FL rankings reflect theexistence of MPs for given contrasts, independent of the frequency with which speakers
use them. FL “is represented by” the number of words (i.e., the types) or the numberof pairs of words that it serves to keep distinct (Catford, 1987, p. 88). This means that
his method gives equal value to all words, whether common words such as “say”, “sit”,“sick”, and “soap” or rare words such as “sib” (which he tells us may be known only to
Scots like him) or “cepe” (which he tells us he failed to include because he did not know
it at the time). With this in mind, the compilation of his FL rankings was approached22

Vowel and Consonant Contrasts

by first identifying phonemic oppositions “that differ from each other by one or two
distinctive features” and then listing all the simple phonological monosyllables in his
own pronunciation that embody those oppositions. Furthermore, Catford (1988, p. 19) isforthright in pointing out that the measures he provides are “a personal count, with thelimitations and idiosyncrasies that that implies” (italics in the original). In order to workthrough all the possible combinations in a systematic manner, he filled in a matrix foreach initial consonant with vowels listed down the left side and final consonants acrossthe top. Oppositions were found by comparing matrices.
The Relative Functional Load list provided in Catford (1987) contains 158
phonological oppositions—57 initial consonants, 44 final consonants, and 57 vowels.
The contrast that differentiated the largest number of words was assigned a value of
100% and the work done by other contrasts was measured related to it.

2.3 Challenges and opportunities for replica studies
As shown, these antecedent works have set up certain expectations when it comes tothis kind of FL research. Specifically:•

There is consensus that vowel and consonant contrasts matter in instruction (Brown,
1988; Catford, 1987) and assessment (viz., Kang & Moran, 2014; Munro & Derwing,
2006; Suzukida & Saito, 2019). In the case of instruction, the presentation ofphonemes as contrasts (rather than isolated individual items) enhances and facilitates
the identification and learning of the elements of the sound system. In the case of
assessment, it is proposed that phonemic contrasts play a role in intelligibility andcomprehensibility.

•

There is consensus that MPs matter in linguistic theory (Levis & Cortes, 2008) andin instruction (Brown, 1988; Catford, 1987). In linguistic theory, MPs embody thefunctional role of phonemes as “bearers of meaning in the given language” (Vachek
et al., 2003, p. 120). MPs are “one of the most commonly used forms to demonstratephonemic categories in any language” and have been a “mainstay” for teachingpronunciation and assessing spoken language production, as Levis and Cortes(2008, p. 197) observe. In instruction, both Brown and Catford implicitly value MPs,
perhaps disproportionately, as they single out the number of MPs (as types) as thebasis for FL rankings.

•

There is consensus that sequencing matters in learning and assessment. Textbooks,

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No. 47course syllabi, and curricula embody decisions made by materials designers andteachers as well as administrators regarding the order in which selected features
should be taught. Leveling schemes like CEFR are indicative of a perceived hierarchyof mastery with higher levels encompassing those skills associated with lower
levels. Rubrics are an example of learning and assessment tools which associatequalitative descriptors of perceived degree of aptitude and scalar evaluations suchas advanced-intermediate-novice. It is worth noting that major commercial ELT
textbook publishers such as Cambridge University Press, PearsonELT, and Oxford
University Press have adopted corpus-based approaches to production since the2000s and market their products as following selection and sequencing that betterreflect actual language use.
•

There is a consensus that FL measures that reflect usage frequency can be useful inguiding selection and sequencing in the domain of pronunciation teaching. Brown(1988) prefaces his work with a mention of this issue when he refers to the dilemmateachers must confront regarding what merits precious class time. Catford expresses
a similar view when he proposes frequency and FL as two guiding principles
for selection. Munro and Derwing (2006, p. 530) echo these sentiments based on
findings from their study, suggesting that FL “provides a framework for deciding”
how to allocate instructional resources.
This review of the Brown and Catford rankings has made some challenges for

replica studies apparent. One point of challenge is the provenance of the data, which is
unknown in Brown’s case and unretrievable in Catford’s case. The analytical procedures
present another challenge since there are ambiguities and gaps in Brown’s explanation
while Catford’s approach of counting MPs has been superseded, as he hoped.
We are thus provided with an opportunity to devise a methodological approach
which meets the expectations just discussed and replicates the intentions (rather than theprocedures) of Brown and Catford. The next section elaborates upon the present study.

3 The present study
The present work takes impetus from the substantial number of studies which adopt
information-theoretic approaches to the estimation of FL (e.g., Oh et al., 2015; Surendran24

Vowel and Consonant Contrasts& Niyogi, 2003, 2006; Wedel et al., 2013). This approach, first formulated by Hockett(1955), quantifies the amount of information conveyed by language in terms of Shannon’s
entropy (Shannon, 1948). Hockett (1966, p. 8) proposed that a phonemic system has “ajob to do” and that it is possible to quantify the work done by a given constituent bycomparing the entropy of the system with and without that constituent. Surendran andNiyogi (2003, 2006) demonstrated the usefulness of this approach in estimating theinformation value of a wide range of linguistic units including phonemes, phonemic
contrasts, tone, stress in various languages. Results from cross-linguistic informationtheoretic FL analyses of phonological components reported by Oh and colleagues (2015)
have contributed data-driven insights to discussions regarding the organization of themental lexicon and Wedel and colleagues (2013) have provided statistical evidence of FL
as a factor in diachronic sound change.

3.1 Data set
The data set used in this study was curated from the British Academic Spoken
English (BASE) corpus (https://www.reading.ac.uk/acadepts/ll/base_corpus/). The
corpus contains 1.64 million running words sampled from university contexts, specificallyrecordings of 160 lectures and 39 seminars in a variety of departments. For the purposesof the present investigation, the highly frequently recurring words (HFWs) were identified
and phonemic transcriptions were manufactured. Gilner and Morales (2020) document
the rationale and procedures undertaken for the lexical analyses. Suffice it to say, therationale draws on the well-attested phenomenon of high-frequency vocabulary (Biber &Conrad, 2010; Faucett et al., 1936; Nation, 2001; Schmitt & Schmitt, 2014; Sinclair, 1991)
along with the well-documented frequency effects in learning (e.g., Ellis, 2002; The Five
Graces Group et al., 2009) as well as speech processing and cognition (e.g., Brysbaert
et al., 2018; Divjak & Caldwell-Harris, 2015). Procedural details on the manufacture of
the phonological word forms are described in Gilner (2020). A review of these previous
works will demonstrate that utmost care was taken to overcome the difficulties ofworking with electronic corpora and that particular attention was paid to achieving
reliable and consistent phonemic transcriptions, including the development of custom
software6.

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3.2 Calculation of FL
As mentioned previously, two entropy measures are calculated: one that corresponds
to the information or entropy of the system containing all of its constituents and one that
corresponds to the entropy of the system without a given constituent. The difference
between the two measures corresponds to the FL of the particular constituent. Equation
1 calculates the entropy of the system—the measure ‫— )ܮ(ܪ‬in terms of the probabilityof word-forms (‫݌‬௪೔ ) as a factor of the recurrence of a word in a corpus.
ேಽ

H(L) = െ ෍ ‫݌‬௪೔ ‫ כ‬log ଶ (‫݌‬௪೔ )௜ୀଵ

Equation 1. Amount of information or entropy in language L

The FL of a phoneme pairing φ-ψ is defined as the difference between the entropy‫ )ܮ(ܪ‬of the initial system and the entropy ‫כܮ(ܪ‬ఝట ) of the system where two sounds havemerged, as shown in Equation 2.
‫ܮܨ‬஦,ந = ‫כܮ(ܪ – )ܮ(ܪ‬ఝట )Equation 2. Functional load of the contrast between two phonemes φ and ψ

3.3 Complementary measures
In the presentation of results that follows, two complementary normalization
measures are presented alongside the raw FL measures, namely DRN and LDRN. DRN,
or dominant relative normalization, expresses FL as a fraction of the constituent withthe highest FL. This is the method generally found in the literature (e.g., Catford, 1987;
Gilner & Morales, 2020; Herdan, 1958). LDRN, or least dominant relative normalization,
expresses the FL of each constituent as a magnitude of the one with the lowest FL. Notethat these two measures express equivalent ratios as shown in Equation 3.

a) ‫ܴܰܦ‬ఝ =௑ക௑ಾb) ‫ܴܰܦܮ‬ఝ =

=

௑ക
௑೘

௅஽ோேക
௅஽ோேಾ

=

஽ோேക
஽ோே೘

Equation 3. Equivalent relationships between DRN and LDRN

26

Vowel and Consonant Contrasts

4

Results
The results presented here are based on 1,493,460 phonemic transcriptions,manufactured according to the phonological specifications provided in Upton (2004).
According to Upton’s specifications, BRP has 21 vowel phonemes and 24 consonant
phonemes and, thus, the maximum number of possible vowel contrasts is 210 (=and the maximum number of possible consonant contrasts is 276 (=ଶଵ × ଶ଴

ଶସ × ଶଷ
ଶଶ)). The data

set instantiated 137 vowel contrasts and 198 consonant contrasts. The top 40 contrasts,
the maximum number that could be fit on one page, are presented in the tables in thismanuscript. Interested readers can find complete results in the companion spreadsheet
available on ResearchGate.

4.1 Vowel contrasts
Table 1 indicates a rather uneven distribution of work among the vowel contrasts.
LDRN values show that the top ranked /ɪ - æ/ obtains an FL that is 12.67 times greaterthan the 40th ranked /eɪ - ɜ:/. DRN values further expose some stark differences in therelative amount work carried by contrasts. The 5th ranked contrast does 55.72% of thework that the 1st ranked contrast. The relative decrease continues down the list: the 10th
ranked does 34.47% of the work that the 1st does, the 15th ranked does 19.03%, the 20th
ranked does 15.69%, the 25th does 13.20%, the 30th does 11.33%, the 35th does 8.90%, andthe 40th does 7.89% of the top ranked contrast. In other words, the decrease in relative
amount of work is steady with markedly larger decreases at the top of the ranking.
Closer scrutiny reveals a dominant role of certain vowel phonemes. The phoneme/eɪ/ participates in 9 contrasts (among the top 40), 7 of which are among the top
20. Furthermore, several of these involve phoneme pairs that are rather similar in
articulatory terms. The phonemes involved in the 2nd ranked contrast /eɪ - ʌɪ/ differ along
only one primary dimension, that of degree of tongue retraction. The phonemes involvedin the 10th ranked contrast /eɪ - ɛ:/ differ in terms of tongue height and lengthening. The
phoneme /i/ participates in 9 contrasts, 3 of which are among the top 20. The phoneme/ɔ:/ participates in 8 contrasts, 6 are among the top 20. The phonemes /əʊ aʊ ɪ/ participate
in 6 contrasts, the latter of which has 3 among the top 20. The phoneme /ʌɪ/ participatesin 5 contrasts, 4 of which are among the top 20.
Several other contrasts are rather similar in articulatory terms. Twelve of the 40

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Table 1. FL ranking of the top 40 vowel contrasts in BRP
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Phoneme contrast
ɪ
æ
eɪ
ʌɪ
eɪ
ɑ:
ɛ:
ə
eɪ
ə
eɪ
ɔ:
ɔ:
ɪ
ʌɪ
ɑ:
ʌɪ
ɔ:
eɪ
ɛ:
ʌɪ
i
ɔ:
ɑ:
eɪ
i
i
ɜ:
ɔ:
u:
eɪ
əʊ
ɔ:
æ
ɪ
aʊ
æ
ɛ
u:
ɪə
ɪ
ɛ
i
əʊ
ɛ
ɒ
i
ɛ:
i
u:
əʊ
aʊ
eɪ
ʌ
aʊ
u:
ɛ
ʌ
ʌɪ
ɜ:
i
ɪə
æ
aʊ
ɔ:
i
i
aʊ
aʊ
ɪə
ɪ
ʌ
ɪ
əʊ
ɔ:
əʊ
əʊ
ɪ:
eɪ
ɜ:

FL
0.06550.05000.03770.0376
0.03650.03250.03030.02880.02360.02260.01950.01820.01430.01290.01250.01200.01170.01070.01040.01030.01020.00970.00910.00910.00860.00850.00800.00770.00770.00740.00680.00680.00670.00670.00580.00560.00560.00550.00550.0052

28

DRN
100%
76.38%
57.58%
57.43%
55.72%
49.67%
46.27%
44.03%
36.09%
34.47%
29.81%
27.75%
21.80%
19.72%
19.03%
18.26%
17.86%
16.26%
15.95%
15.69%
15.64%
14.79%
13.96%
13.85%
13.20%
12.91%
12.16%
11.78%
11.76%
11.33%
10.42%
10.33%
10.27%
10.23%
8.90%
8.54%
8.48%
8.44%
8.38%
7.89%

LDRN
12.67
9.68
7.30
7.28
7.06
6.29
5.86
5.58
4.57
4.37
3.78
3.52
2.76
2.50
2.41
2.31
2.26
2.06
2.02
1.99
1.98
1.87
1.77
1.75
1.67
1.64
1.54
1.49
1.49
1.44
1.32
1.31
1.30
1.30
1.13
1.08
1.07
1.07
1.06
1.00

Vowel and Consonant Contrasts

differ primarily in terms of degree of tongue height. This is notably the case for the 1st
ranked contrast between the high-front and low-front phonemes. Other anterior-based
examples include the contrasts ranked 10th, 13th, 19th, 21st, and 24th. The highest ranked
contrast between posterior-based phonemes is ranked 9th. Other examples are ranked 12th,
15th, and 38th. Four of the top 10 contrasts involve phonemes that differ primarily in termsof tongue retraction. The 2nd ranked contrast involves two anterior-closing diphthongs
whose initiating segments occupy opposite quadrants in the mid zone of vowel space.
Similarly, the contrasts ranked 4th, 5th, and 6th pair mid-front with mid-central and midback phonemes.

4.2 Consonant contrasts
Table 2 indicates an uneven distribution of work among the consonant contrasts.
LDRN values show that the top ranked /n - z/ obtains an FL that is 8.51 times greater than
the 40th ranked /z - m/. DRN values further expose some stark differences in the relative
amount work carried by contrasts. The 5th ranked contrast does 45.16% of the work thatthe 1st ranked contrast. The relative decrease continues down the list: the 10th ranked
contrast does 31.78% of the work that the 1st does, the 15th ranked does 25.00%, the 20th
ranked does 18.18%, the 25th does 16.94%, the 30th does 14.57%, the 35th does 13.82%, andthe 40th does 11.75% of the top ranked contrast. In other words, the decrease in relative
amount of work is steady with larger decreases at the top of the rank. It is worth notingthat the >50% threshold used to classify high FL in recent studies (viz., Kang & Moran,
2014; Munro & Derwing, 2006; Suzukida & Saito, 2019) would be satisfied by the top 4
contrasts in this ranking (and the top 5 in the case of vowel contrasts).
Closer scrutiny reveals a dominant role of certain consonant phonemes. The
phoneme /w/ participates in 9 contrasts (among the top 40), 5 of which are among the top
20. The phoneme /n/ participates in 8 contrasts, 7 of which are among the top 20. The
phoneme /t/ participates in 8 contrasts, 6 of which are among the top 20. The phoneme/z/ participates in 6 contrasts, with 4 among the top 20. The phoneme /m/ participates in
6 contrasts, 1 of which is among the top 20.
The contrasts in this table tend to involve rather distinct phonemes which differ
in terms of both manner and place of articulation. Only seven out of the 40 contrasts
in Table 2 involve phonemes that are relatively similar. The phonemes involved in thecontrast ranked 5th, for example, differ only in voicing. The 6th ranked contrast pairs the

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Table 2. FL ranking of the top 40 consonant contrasts in BRP
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Phoneme contrast
n
z
t
n
t
z
t
j
t
d
z
f
n
f
n
l
d
j
t
f
w
b
n
w
n
g
n
s
w
ð
w
h
w
s
z
d
t
m
h
b
n
m
w
g
w
m
j
h
v
p
s
m
w
d
t
s
t
h
l
ʧ
s
g
z
v
θ
ʧ
l
θ
s
ð
f
m
w
ʃ
d
v
s
k
z
m

FL
0.07700.07420.0687
0.0566
0.03480.02820.02700.02590.02550.02450.02340.01990.01990.01970.01930.01860.01590.01520.01510.01400.01390.01380.01360.01330.01300.01300.01250.01250.01220.01120.01120.01080.01080.01080.01060.01030.01000.00950.00910.0090

30

DRN
100%
96.35%
89.24%
73.49%
45.16%
36.65%
35.01%
33.60%
33.12%
31.78%
30.39%
25.86%
25.82%
25.58%
25.00%
24.13%
20.65%
19.80%
19.59%
18.18%
18.07%
17.89%
17.70%
17.24%
16.94%
16.92%
16.26%
16.19%
15.86%
14.57%
14.54%
14.06%
13.99%
13.98%
13.82%
13.41%
13.02%
12.36%
11.80%
11.75%

LDRN
8.51
8.20
7.60
6.26
3.84
3.12
2.98
2.86
2.82
2.71
2.59
2.20
2.20
2.18
2.13
2.05
1.76
1.69
1.67
1.55
1.54
1.52
1.51
1.47
1.44
1.44
1.38
1.38
1.35
1.24
1.24
1.20
1.19
1.19
1.18
1.14
1.11
1.05
1.00
1.00

Vowel and Consonant Contrasts

voiced alveolar and voiceless labiodental fricative while the 32nd ranked contrast involves
the voiced labiodental and the voiced alveolar fricatives. The 8th ranked contrast pairs thelateral approximant with the alveolar nasal. The 21st ranked contrast involves the bilabial
and alveolar nasals. The 11th and 22nd ranked contrasts involve the voiced labial-velar
approximant paired with the voiced bilabial stop in the former case and with the voiced
velar stop in the latter case.
At this point, the objectives of this manuscript stated in the Introduction have beenaccomplished. The review of the work of Brown and Catford exposed some obstacles toreplication and prompted the design and implementation of an updated approach to the
production of FL rankings. The present study produced FL rankings for 137 vowel and198 consonant contrasts of BRP estimated from usage metrics in the BASE corpus, thetop 40 of which were introduced here. The companion spreadsheet available throughResearchGate provides the field with the complete results.

5 Addendums
This section includes three addendums which serve to further contextualize theresults of this study. The first addendum addresses the issue of relative frequency ofrecurrence among the words that form MPs. Next, readers are guided through someobservations regarding how to interpret differences in past and present FL rankings.
Lastly, the FL rankings for vowel and consonant contrasts in General American English(GAE) are presented.

5.1

Balanced vs unbalanced MPs
Given the role that MPs play in the of estimation of FL, a shared concern among

researchers has been accounting for the frequency of use of the words that form MPs.
Intuitively, it seems sensible to consider that all things being equal, “a contrast which
distinguishes two frequent forms is more significant than one which distinguishes two
infrequent forms, or a frequent from an infrequent one.” (Catford, 1988, p. 4, citing
Greenberg [1958]). This concern is understandable since, depending on the line of inquiry,
the relative contributions of lexical items might need to be taken into consideration wheninterpreting results. It is thus important to acknowledge that methods of estimating FL
intended to reflect the variable of relative contribution have not yet been devised. This

31

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No. 47means that MPs formed between two words with similar probability of occurrence,
between a highly recurrent word and a rarely recurrent one, or two words of low
probability of occurrence all contribute equally to the FL estimation.
The methodology adopted for the present investigation goes some way toward
addressing this issue. Recall that the FL values are derived from the MPs formed among
HFWs. A consequence of this methodological decision is the exclusion of MPs involving
words with low probability of recurrence in the corpus as a whole while, at the same time,narrowing the magnitude of differences in probabilities among the words included. In
this way, the FL rankings presented here might provide interested readers with a meansby which to explore the hypotheses put forward by Levis and Cortes (2008, p. 205)
regarding “the effect of frequency on using minimal pairs”.7

5.2 Catford’s ranking in light of the findings from the present study
As the differences in data and methodology impede meaningful comparison of theresults obtained from this study with the rankings produced by Catford, this addendum
is provided simply to orient those readers familiar with Catford’s rankings with theextent of the differences. Table 3 presents a list of the top 40 initial consonant contrasts
provided in Catford’s ranking including the DNR values obtained from this usage-driven,
information-theoretic approach to calculation in the rightmost column.
The divergences in FL measures are immediately obvious, as expected. Some of thepairs obtain low or nil FL when usage probabilities are taken into consideration. Twelve
contrasts on this list obtain an FL <1.0%, including three of the top 5. Recall that an FLof 0.00% reflects an absence of MPs in the data set. Researchers using FL to investigate
comprehensibility have followed Munro and Derwing (2006) in applying a thresholdof >50% to distinguish between to “high FL errors” and “low FL errors”. Results fromthe present study indicate that three of the contrasts on this list satisfy the criterion of
FL >50% and only one among them, namely /n – l/, was a variable of interest in thecomprehensibility studies just mentioned.
Some of the differences in results at the top of the list merit particular attention. The
contrasts /b – p/, /k – p/, and /t – p/ are ranked 2nd, 3rd, and 4th, respectively, on Catford’slist. They obtain very little or nil FL in the present investigation. This seems somehow
counterintuitive since examples of MPs for each of these three contrasts come easily to
mind. In other words, they are type-rich contrasts and this type-richness creates a (false)32Vowel and Consonant Contrasts
Table 3. Catford’s list of initial consonants and DRN values from the present study
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Phoneme contrast
h
k
b
p
k
p
t
p
h
p
s
h
l
ɹ
d
b
t
s
t
k
d
l
f
p
w
b
d
ɹ
t
d
g
b
f
h
s
f
n
l
n
m
d
g
n
d
s
ʃ
g
k
w
g
n
ɹ
d
ʤ
t
ʧ
s
ʧ
g
ʤ
b
v
ʃ
ʧ
f
v
w
v
s
θ
j
ʤ
d
ð
ʧ
ʤ
t
θ
f
θ

33

Catford (1987)
100%
98%
92%
87%
85%
85%
83%
82%
81%
81%
79%
77%
76%
75%
73%
71%
69%
64%
61%
59%
56%
53%
53%
50%
49%
41%
39%
39%
37%
31%
29%
26%
23%
22%
21%
21%
19%
19%
18%
15%

Present study
4.32%
0.00%
0.90%
0.00%
6.63%
19.94%
9.24%
1.99%
35.84%
6.91%
14.32%
4.67%
67.28%
7.26%
100.00%
1.78%
0.89%
8.62%
74.39%
40.00%
0.66%
20.80%
17.85%
10.21%
39.60%
8.14%
0.72%
2.11%
0.09%
0.00%
0.00%
1.89%
8.67%
0.00%
8.79%
0.00%
6.13%
0.00%
6.14%
2.99%

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perception of high FL. When usage metrics are used to estimate FL, however, it turns
out that intuitions stemming from type-based perceptions do not coincide with actual
language use.

5.3

FL rankings for vowel and consonant contrasts in General American
English (GAE)
Until now, the field has had access to rankings reflective of a single English variety,namely, BRP. This section presents FL rankings for vowel and consonant contrasts for
General American English (GAE). The data set was curated from the MICASE corpus(Simpson et al., 2002), which functions as a companion to BASE and contains close to
200 hours of academic speech from university departments. Analytical procedures mirror
those described previously regarding the BRP rankings. The results presented here arebased on 1,350,474 phonemic transcriptions of the dominant vocabulary identified in the
MICASE corpus manufactured according to the phonological specifications provided
in Yavaş (2006). According to these specifications, GAE has 16 vowel phonemes and
24 consonant phonemes and, thus, the maximum number of possible vowel contrasts
is 120 (=(=ଶସ × ଶଷ
ଶଵ଺ × ଵହ
ଶ) and the maximum number of possible consonant contrasts is 276). The data set instantiated 86 vowel contrasts and 195 consonant contrasts. The

top 40 contrasts, the maximum number that would fit on one page, are presented in thetables below. Interested readers are reminded that they can find complete results in thecompanion spreadsheet.

5.3.1 Vowels contrasts
Table 4 indicates a rather uneven distribution of work among the vowel contrasts.
LDRN values show that the top ranked contrast /eɪ - aɪ/ obtains an FL that is 16.16 times
greater than the 40th ranked /ɪ - ʌ/. DRN values further expose some stark differences in
the relative amount work carried by contrasts. The 5th ranked contrast does 44.20% of thework that the 1st ranked contrast. The relative decrease continues down the list: the 10th
ranked does 22.60% of the work that the 1st does, the 15th ranked does 16.41%, the 20th
ranked does 13.22%, the 25th does 9.20%, the 30th does 8.21%, the 35th does 7.09%, andthe 40th does 6.19% of the top ranked contrast. In other words, the decrease in relative
amount of work is steady with markedly larger decreases at the top of the rank.
Closer scrutiny reveals a dominant role of certain vowel phonemes. The phonemes

34Vowel and Consonant Contrasts
Table 4. FL ranking of the top 40 vowel contrasts in GAE
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Phoneme contrast
eɪ
aɪ
ɪ
æ
eɪ
ə
ɪ
ɔ
æ
u
aɪ
i
eɪ
i
i
oʊ
ɔ
ɑ
eɪ
oʊ
ɪ
aʊ
ɪ
ɛ
ɛ
ɑ
æ
ɛ
oʊ
aʊ
æ
ɔ
ɛ
ʌ
eɪ
ʌ
i
u
i
aʊ
aʊ
u
æ
aʊ
aɪ
ʊ
aʊ
ɑ
oʊ
u
æ
i
ɔ
oʊ
ɔ
aʊ
aɪ
ɛ
aɪ
ɑ
ɛ
ɜ
eɪ
ɔ
oʊ
ə
aɪ
oʊ
eɪ
ɪ
aɪ
u
ɪ
oʊ
eɪ
u
ɪ
ɜ
ɪ
ʌ

FL
0.05830.05540.03570.02740.02580.02310.01910.01840.01810.01320.01280.01010.01000.00960.00960.00880.00880.00880.00870.00770.00750.00710.00660.00620.00540.00520.00500.00500.00500.00480.00470.00460.00430.00420.00410.00400.00380.00380.00360.0036

35

DRN
100%
95.03%
61.28%
47.10%
44.20%
39.60%
32.70%
31.56%
30.98%
22.60%
21.92%
17.40%
17.12%
16.55%
16.41%
15.10%
15.08%
15.08%
14.90%
13.22%
12.79%
12.23%
11.37%
10.70%
9.20%
8.86%
8.63%
8.63%
8.62%
8.21%
8.06%
7.90%
7.32%
7.24%
7.09%
6.87%
6.53%
6.46%
6.26%
6.19%

LDRN
16.16
15.36
9.90
7.61
7.14
6.40
5.28
5.10
5.01
3.65
3.54
2.81
2.77
2.67
2.65
2.44
2.44
2.44
2.41
2.14
2.07
1.98
1.84
1.73
1.49
1.43
1.39
1.39
1.39
1.33
1.30
1.28
1.18
1.17
1.15
1.11
1.06
1.04
1.01
1.00

愛知大学

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No. 47/eɪ ɪ oʊ/ participate in 8 contrasts among the top 40. The phoneme /aɪ/ participates in 7
contrasts. The phonemes /aɪ aʊ/ participate in 7 contrasts. The phonemes /æ i ɔ oʊ ɛu/ participate in 6 contrasts.
Several contrasts are rather similar in articulatory terms. Eight of the 40 differ
primarily in terms of degree of tongue height. A prominent example is the 2nd ranked
contrast between the high-front and low-front phonemes. Other anterior-based examples
include the contrasts ranked 7th, 12th, 14th, 26th, and. The highest ranked contrast between
posterior-based phonemes is ranked 9th. Other examples are ranked 25th and 27th.

5.3.2 Consonant contrasts
Table 5 indicates an uneven distribution of work among the consonant contrasts.
LDRN values show that the top ranked /t - z/ obtains an FL that is 7.73 times greaterthan the 40th ranked /z - m/. DRN values further expose some stark differences in therelative amount work carried by contrasts. The 5th ranked contrast does 54.66% of thework that the 1st ranked contrast. The relative decrease continues down the list: the 10th
ranked contrast does 36.89% of the work that the 1st does, the 15th ranked does 29.07%,
the 20th ranked does 23.20%, the 25th does 19.54%, the 30th does 16.97%, the 35th does
15.49%, and the 40th does 12.94% of the top ranked contrast. In other words, the decrease
in relative amount of work is steady with larger decreases at the top of the rank.
Closer scrutiny reveals a dominant role of certain consonant phonemes. The phoneme/n/ participates in 9 contrasts (among the top 40), 8 of which are among the top 20. The
phoneme /w/ also participates in 9 contrasts (among the top 40), 6 of which are among the
top 20. The phoneme /t/ participates in 8 contrasts, 5 of which is among the top 20. The
phoneme /m/ also participates in 8 contrasts, 1 is among the top 20. The phonemes /z s/
participate in 6 contrasts, with 3 and 2 in the top 20 respectively. The phonemes /d f g h/each participate in 4 contrasts among the top 40.
The contrasts in this table tend to involve rather distinct phonemes which differ
in terms of both manner and place of articulation. Only four out of the 40 contrasts
in Table 5 involve phonemes that are relatively similar. The contrast ranked 5th, forexample, pairs voiced and voiceless alveolar plosives. The 10th ranked contrast pairs thealveolar nasal and lateral approximant while the 16th ranked contrast involves the alveolar
lateral approximant and alveolar approximant. The 8th ranked contrast pairs the lateralapproximant with the alveolar nasal. The 22nd ranked contrast involves the bilabial and36

Vowel and Consonant Contrasts
Table 5. FL ranking of the top 40 consonant contrasts in GAE
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40

Phoneme contrast
t
z
n
z
n
t
t
j
t
d
d
j
n
ɹ
z
f
n
s
n
l
n
w
n
f
t
f
w
b
w
ð
l
ɹ
w
h
n
g
w
m
w
s
t
m
n
m
m
ɹ
z
d
h
b
w
d
j
h
w
ʃ
v
p
s
ð
s
g
m
s
m
b
w
g
t
s
t
h
m
f
l
g
z
v
z
m

FL
0.07230.07130.06800.06160.03950.03310.03120.02700.02700.02670.02450.02390.02330.0211
0.02100.01930.01910.01810.01710.01680.01610.01580.01450.01420.01410.01320.01300.01300.01250.01230.01210.01210.01200.01160.01120.01080.01020.00970.00960.0094

37

DRN
100%
98.62%
94.01%
85.15%
54.66%
45.73%
43.12%
37.38%
37.34%
36.89%
33.95%
32.99%
32.26%
29.19%
29.07%
26.66%
26.48%
25.02%
23.59%
23.20%
22.22%
21.81%
19.99%
19.68%
19.54%
18.27%
18.01%
17.95%
17.22%
16.97%
16.74%
16.72%
16.54%
16.03%
15.49%
14.89%
14.14%
13.46%
13.23%
12.94%

LDRN
7.73
7.62
7.27
6.58
4.22
3.53
3.33
2.89
2.89
2.85
2.62
2.55
2.49
2.26
2.25
2.06
2.05
1.93
1.82
1.79
1.72
1.69
1.55
1.52
1.51
1.41
1.39
1.39
1.33
1.31
1.29
1.29
1.28
1.24
1.20
1.15
1.09
1.04
1.02
1.00

愛知大学

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alveolar nasal phonemes.

6 Closing remarks
FL has long held the interest of applied linguists, yet the go-to resources forteachers and researchers remain FL rankings for BRP published in the 1980s. The review
provided in this manuscript of the steps taken to create those rankings has demonstrated
the need for new approaches to the production of these resources. The corpus-driven
methodology described here is one alternative and the results have provided a very
different portrayal of the relative amount of work undertaken by vowel and consonant
contrasts than that obtained from type-based methods (such as the one used by Catford).
In addition, differences in results obtained for BRP and GAE indicate that FL appears
to be a system-specific phenomenon, highlighting a venue of inquiry worthy of pursuit.
The methodology used in the present study can be replicated, thereby, facilitating the
expansion of the rankings available. A welcome outcome of this study would be further
investigation into the development and application of FL rankings in order to broaden
and deepen understanding of the role FL plays in communication and, perhaps, speechprocessing. The companion spreadsheet available on ResearchGate provides complete
results of the two varieties discussed here as well 8 other varieties, namely, CanadianEnglish, East African English, Hong Kong English, Indian English, Irish English,
Jamaican English, Philippine English, and Singapore English.
Acknowledgements
I am grateful to Franc Morales for sharing observations and insights which encouraged a morecomprehensive presentation of this material.

Notes
1
2
3
4

This work was reproduced as Brown (1991).
The steps taken to create the Relative Functional Load list provided in this work are described in
Catford (1988).
Brown’s paper offers no further explanation or empirical support for his choice of pairs.
Denes (1964) provides phoneme frequency metrics obtained from analyses of an electronic
corpus compiled from two phonetic readers containing a total of 23,052 words composed of38

Vowel and Consonant Contrasts

5

6
7

72,210 phonemes transcribed according to a BRP pronunciation model.
For example, pairs /e, æ/ and /æ, ʌ/ are both given a rank of 10. According to Denes (1964), adding
cumulative frequencies from Table 2 and number of MPs from Table 7b yields 233.34 = ((2.81 +1.53) + 229) and 119.2 = ((1.53 + 1.67) + 116), respectively.
This work was supported by JSPS KAKEN Grant Number JP16K02776.
The BASE-UK-DOVO word list is available at https://leo.aichi-u.ac.jp/~gilner/wordlists.html.
This file contains frequency and part-of-speech information.

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