Predicting phonotactic difficulty in second language acquisition

1
Predicting phonotactic difficulty in second
language acquisition

• Katarzyna Dziubalska-Kolaczyk
• Adam Mickiewicz University, Poznan
• dkasia_at_ifa.amu.edu.pl

2
Predicting phonotactic difficulty in second
language acquisition

• Katarzyna Dziubalska-Kolaczyk
• Grzegorz Krynicki
• Adam Mickiewicz University, Poznan
• dkasia_at_ifa.amu.edu.pl
• krynicki_at_ifa.amu.edu.pl

3
Aim of the paper

• to demonstrate that
• universal phonotactic preferences guide the
  acquisition of consonant clusters in a second
  language

4
Empirical evidence

• young learners of English (L2 English) with the
  following L1s
• independent Japanese, Korean, Vietnamese
• Sino-Tibetan Chinese
• Austronesian Kosraean, Marshallese, Palauan,
  Ponapean, Samoan, Tagalog, Trukese, Visayan
• Dravidian Tamil
• Polish

5
Outline of the talk

1. Hypothesis
2. Description of the experiment
3. Introduction to BB phonotactics
4. Phonotactic calculator
5. Analysis of the selected data
6. Preliminary conclusions

6
Hypothesis

• a degree of difficulty in pronouncing L2 clusters
  would correlate with the universal
  characteristics of a given consonantal cluster
• the more preferred a cluster, the easier and less
  susceptible to modifications it is expected to be
• NAD is expected to be a universal criterion,
  underlying the performance of all subjects, and
  surpassing other relevant factors, such as the
  structure of the subjects mother tongue, their
  experience with English or their other capacities
  and motivations
• degree of preference is measured by the NAD
  Principle

7
Description of the experiment

• 53 subjects 15 subjects analysed here
• aged 11-13
• native speakers of 15 various languages 10 here
• recorded reading 83 times an English carrier
  sentence I havent seen a xxx before! each time
  containing a different bi-syllabic nonce word
• each word contained just one double or triple
  consonant cluster
• all positions (initial, medial and final) and
  representative combinations were covered

8
Text for subjects

• Read the following sentences aloud
• I havent seen a kyati before!
• I havent seen a shwepy before!
• I havent seen a chluppy before!
• I havent seen a katewt before!
• I havent seen a petewm before!

9
a sound file demo

• a Ponapean speaker (Micronesia)

10
BB phonotactics

• a universal model of phonotactics within Beats
  Binding Phonology (Dziubalska-Kolaczyk 2002) a
  syllable-less theory of phonology embedded in
  Natural Phonology
• intersegmental cohesion determines syllable
  structure, rather than being determined by it (if
  one insists on the notion of the syllable)

11
BB phonotactics

• the phonotactic preferences specify the
  universally required distances between segments
  within clusters which guarantee, if respected,
  preservation of clusters (cf. intersegmental
  cohesion)
• clusters, in order to survive, must be sustained
  by some force counteracting the overwhelming
  tendency to reduce towards CV's (CV preference)
• this force is a perceptual contrast defined as
  NAD Principle (cf. Dziubalska-Kolaczyk 2002,
  2003, Dressler Dziubalska-Kolaczyk 2007, in
  press, Dziubalska-Kolaczyk Krynicki 2007,
  Bertinetto et al. 2007)

11
12
BB phonotactics

• the universal preferences specify the optimal
  shape of a particular cluster in a given position
  by referring to the
• Net Auditory Distance Principle (NAD Principle)?
• NAD MOA POA Lx
• whereby MOA, POA and LX are the absolute values
  of differences in the Manner of Articulation,
  Place of Articulation and Voicing of the
  neighbouring sounds respectively

12
13
BB phonotactics

• Example
• NAD (C1,C2) NAD (C2,V)?
• In word-initial double clusters, the net auditory
  distance (NAD) between the two consonants should
  be greater than or equal to the net auditory
  distance between a vowel and a consonant
  neighbouring on it.

14
Table of consonants
14
15
BB phonotactics

• consider the preference for initial double
  clusters
• NAD (C1,C2) NAD (C2,V)?
• let us now define two Net Auditory Distances
  between the sounds (C1, C2) and (C2, V) where
• C1 (MOA1, POA1, Lx1)
• C2 (MOA2, POA2, Lx2)
• V (MOA3, Lx3)
• in terms of the following metric for (C1, C2)
  cluster
• MOA1 - MOA2 POA1 - POA2 Lx1 - Lx2
• MOA2 MOA3 Lx2 Lx3
• for (C2, V) cluster

15
16
BB phonotactics

• Example
• in CCV in E. try
• t (4, 2, 0), r (1, 2, 1), V (0, 0, 1)?
• NAD (C1, C2) 4-1 2-2 0-1 3014
• NAD (C2, V) 1-0 1-1 101
• thus, the preference
• NAD (C1,C2) NAD (C2,V)?
• is observed because 4 gt 1
• NAD Principle makes finer predictions than the
  ones based exclusively on sonority
• prV gt trV, krV gt trV, trV gt drV, etc.

16
17
BB phonotactics

• the universal NAD Principle leads to predictions
  about language-specific phonotactics, its
  acquisition and change
• specifically, it also allows to predict and
  explain the order of difficulty in the
  acquisition of second language phonotactics which
  appears to be universally valid and as such calls
  for similar remedies across languages

18
English frequent initial doubles according to NAD
Principle
19
Selected Polish clusters according to NAD
Principle
19
20
Phonotactic calculator

• for the purposes of BB phonotactics, Krynicki
  developed the phonotactic calculator
• its purpose is to enable fine-tuning and
  developing the theory by statistical analysis of
  phonetic dictionaries and phonetically annotated
  corpora from various languages

21
Phonotactic Calculator - requirements

• various cluster lengths at all word positions
• formulating phonotactic hypotheses
• feedback on predictability of a phonotactic
  hypothesis
• choice or customization of
• available phone sets, features of each phone and
  scores for each feature
• available phonetic dictionaries and languages
  (PolSynt, Festvox, Festival)
• metrics used for calculating distances between
  phones (taxicab, euclidean)
• accepted phonetic alphabets (IPA, SAMPA)

22
(No Transcript)
23
(No Transcript)
24
(No Transcript)
25
Analysis of the selected data

• a total of 1245 utterances
• produced by 15 children
• each reading 83 sentences containing a nonsense
  word with a 2- or 3-consonant cluster
• in 767 of these utterances (61,6) the speakers
  modified or avoided the cluster that was assumed
  to be the correct pronunciation of the nonsense
  word

26
Error types
error description number of errors in the corpus symbol
vowel insertion between the elements of a consonant cluster or at the end of a cluster that was expected to be pronunced word-finally 234 _at_
reducing the number of consonants in the cluster (from 3 to 2 or 1 and from 2 to 1) 218
unintelligible pronunciation 154 ?
substitution of consonant in a cluster by consonants not present in the expected cluster 152
substantial mispronunciations 119
pause insertion between the elements of a consonant cluster or at the end of a cluster that was expected to be pronunced word-finally 24 .
deletion of the cluster 4 Ø
omission of the word 2 omitted
total 907  
27
Summary statistics for six preferences Summary statistics for six preferences Summary statistics for six preferences
preference number number of cluster that apply to a given preference number of clusters that follow the preference percentage
1 17 17 100
2 13 13 100
3 38 27 71
4 5 3 60
5 5 3 60
6 5 2 40
28
Part 1 of the hypothesis

• A degree of difficulty in pronouncing L2
  clusters correlates with the universal
  characteristics of a given consonantal cluster.
• To a certain degree the amount of correlation
  between the number of errors students make when
  producing a cluster and the NAD parameters
  between the components of that cluster can be
  illustrated by means of cluster ranking in terms
  of their NAD differences and their difficulty.
• Ranking of clusters can be performed first with
  respect to the NAD criterion and then with
  respect to linearly scaled percentage of clusters
  in which speakers made errors.
• Although statistically not significant, the trend
  line indicates the expected direction of change
  and degree of slope between difficulty and NAD
  measure for finals.

29
correlation for final double clusters
30
(No Transcript)
31
Part 2 of the hypothesis Linear Regression

• The more preferred a cluster, the easier and
  less susceptible to modifications it is.
• The error of complex mispronunciation annotated
  in the corpus involved combination of other
  various errors, epenthesis, substitution,
  metathesis and other.
• There is a significant correlation between the
  NAD differences in a word-medial cluster and the
  frequency of the complex mispronunciation errors
  made in it by the speakers (P-value in the ANOVA
  0,0282 R-squared 11,2148).

32
mispronunciation medial clusters
33
Part 2 of the hypothesisAnalysis of variance
and median

• NAD(VC) - NAD(CC) turns out to have statistically
  significant influence on the number of reduction
  errors students made in word-final clusters

34
reduction word-final clusters

Preference?
ANOVA F11.86, p0.006 Kruskal-Wallis T7,46,
p0,006
Difference?
34
35
Part 3 of the hypothesis

• NAD is expected to be a universal criterion,
  underlying the performance of all subjects.
• If a child produces a consonant cluster different
  from the expected one, this new cluster will
  usually follow phonotactic preferences (grand
  mean of 79.7 compared to 78.3 for expected
  clusters).

36
  all all initials initials medials medials finals finals
The number of all expected consonant clusters 83 78,3 22 90,9 43 67,4 18 88,9
The number of expected consonant clusters that followed phonotactic preferences 65 78,3 20 90,9 29 67,4 16 88,9
Total number of elicited consonant clusters 158 79,7 22 53,6 43 60,1 18 58,3
Total number of elicited consonant clusters that followed phonotactic preferences 126 79,7 12 53,6 26 60,1 11 58,3
The number of cases when there was a 0 in the expected cluster but more than 0 in the elicited cluster 10   0   0   0  
The number of cases when both the expected and the elicited cluster were a 1 37   9   20   8  
The number of cases when both the expected and the elicited cluster were a 0 7   0   7   0  
The number of clusters for which no speaker produced an qualifiable utterance. 22   10   14   8  
37

• This suggests that phonotactic preferences
  underlie the performance of the subjects of
  various linguistic backgrounds and may be
  universal.
• More research is necessary to show whether the
  speakers of different languages displayed
  significant differences in their following of the
  preferences.

38
Preliminary conclusions

• universal phonotactic preferences guide speakers
  in producing SL clusters
• the scale of preference in the acquisition of a
  given type of cluster allows for fine-tuning of
  SL learning/teaching materials
• many aspects of the analysis remain to be
  continued
• comparison with the L1s of the subjects
• data from further subjects
• detailed analysis of the errors which types of
  improvements are preferred

39
(No Transcript)
40

• f j a h l a t?? j a t?? w a k j a k r a p l
  a p w a ? w a k m a m j a t l a t?? l a
  s r a l j a m w a t n a
• f j a h l a t?? w a p w a ? w a t n a k j a
  k m a t?? j a t?? l a m w a t l a s r a l
  j a m j a p l a k r a

41
correlation for initial double and triple clusters
41
42
correlation for initial double clusters
43
correlation for medial double clusters