Multiple Sequence Alignment in Historical Linguistics

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1 1 / 32 Multiple Sequence Alignment in Historical Linguistics A Sound Class Based Approach Johann-Mattis List Institute for Romance Languages and Literature Heinrich Heine University Düsseldorf 2011/01/06

2 2 / 32 Structure of the Talk Sequences Alignments Pairwise Sequence Alignment Multiple Sequence Alignment Similarity Sound Classes Main Ideas Working Principle Scoring TPPSR

3 3 / 32 Sequences Alignments - Sequences - - Alignments -

4 4 / 32 Sequences Alignments Sequences Sets Sets are unordered lists of unique objects Sets are compared by comparing the objects of different sets Sequences Sequences are ordered lists of non-unique objects Sequences are compared by comparing both the objects (segments) and the structure of different sequences

5 5 / 32 Alignments Sequences Alignments Sequence Alignment In alignment analyses, the corresponding segments of two or more sequences are ordered in such a way that they are set against each other Segments which do not correspond to any other segments are marked by gaps (-) In this way, both, the structure and the segments of two or more sequences can be compared

6 Alignments Sequences Alignments ʧ ɪ l ɐ vʲ ɛ k ʧ o v ɛ k 1 6 / 32

7 Alignments Sequences Alignments ʧ ɪ l ɐ vʲ ɛ k ʧ o v ɛ k 1 6 / 32

8 Alignments Sequences Alignments ʧ ɪ l ɐ vʲ ɛ k ʧ - - o v ɛ k 1 6 / 32

9 Pairwise Sequence Alignment Multiple Sequence Alignment hjärta cordis herz heart h j - ä r t a - h - e - r z - - h - e a r t - - c - - o r d i s 1 7 / 32

10 8 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Pairwise Sequence Alignment Create a matrix which confronts all segments of two sequences, either with each other, or with gaps Seek the path through the matrix which is of the lowest cost (or the highest score) Calculate the cost (or the score) cumulatively by scoring the matching of segments with segments and with gaps by means of a specific scoring function

11 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T E S T 8

12 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T E S T 6

13 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S - T T - E S T 8

14 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T - E S T 7

15 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E - S T T - - E S T 8

16 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T - - E S T 7

17 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T - E S T T E S T 8

18 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T E S T 6

19 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T - - T - - E S T 5

20 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S - T - - T - - E - S T 6

21 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T - - T - E - S T 5

22 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E - S T - - T - E - - S T 6

23 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T - - T E - - S T 4

24 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T - T E - S T 3

25 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E - S T - T E S - - T 4

26 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T - T E S - T 2

27 9 / 32 Pairwise Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment T E S T T E S T 0

28 10 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignments Guide Tree Heuristics Due to computational restrictions, multiple sequence alignment (MSA) is based on heuristics Heuristics based on guide-trees are the most common ones used in computational biology Based on pairwise alignment scores, a guide-tree is reconstructed, and the sequences are stepwise added to the MSA along it (Feng & Dolittle 1987)

29 11 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment čelovek human člověk human człowiek human čovek human Russian Czech Polish Bulgarian

30 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

31 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

32 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

33 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

34 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ - l o vʲ ɛ k ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

35 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ - l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - o v ɛ k ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

36 11 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ ɪ l ɐ vʲ ɛ k ʧ - l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - o v ɛ k ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

37 12 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment Profiles The guide-tree heuristic can be enhanced by the application of profiles A profile consists of the relative frequency of all segments of an MSA in all its positions, thus, a profile represents an MSA as a sequence of vectors Aligning profiles to profiles instead of aligning two representative sequences of two given MSA yields better results, since more information can be taken into account

38 13 / 32 Pairwise Sequence Alignment Multiple Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ ɪ l ɐ vʲ ɛ k ʧ - l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - o v ɛ k ʧɪlɐvʲɛk Russian ʧlovʲɛk Czech ʧwɔvʲɛk Polish ʧovɛk Bulgarian

39 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k

40 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ 10 ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k

41 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ 25-75

42 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25

43 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25 o 5 ɔ 25 ɐ 25

44 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25 o 5 ɔ 25 ɐ 25 vʲ 75 v 25

45 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25 o 5 ɔ 25 ɐ 25 vʲ 75 v 25 ɛ 10

46 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25 o 5 ɔ 25 ɐ 25 vʲ 75 v 25 ɛ 10 k 10

47 13 / 32 Multiple Sequence Alignment Pairwise Sequence Alignment Multiple Sequence Alignment ʧ ɪ l ɐ vʲ ɛ k ʧ l o vʲ ɛ k ʧ w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ 10 ɪ l 5 w 25 o 5 ɔ 25 ɐ 25 vʲ 75 v 25 ɛ 10 k 10

48 14 / 32 Similarity Sound Classes *ph2tēr *faθēr father 1

49 15 / 32 Similarity Similarity Sound Classes Synchronic Similarity Sounds in different languages are judged to be similar, if they show resemblences regarding the way they are produced or perceived Diachronic Similarity Sounds in different languages are judged to be similar, if they go back to a common ancestor

50 Similarity Sound Classes Similarity Language Word Meaning Mandarin ma⁵⁵ma³ mother German mama mother Russian tak in this way German tʰaːk day 16 / 32

51 Similarity Sound Classes Similarity Language Word Meaning German ʦʰaːn tooth English tʊːθ tooth Italian dɛntɛ tooth French dɑ tooth 16 / 32

52 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n d English t ʊː θ - ** Proto-Indo-European d o n t Italian d ɛ n t ɛ * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

53 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n d English t ʊː θ - ** Proto-Indo-European d o n t Italian d ɛ n t ɛ * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

54 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n d English t ʊː - θ ** Proto-Indo-European d o n t Italian d ɛ n t ə * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

55 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n θ English t ʊː - θ ** Proto-Indo-European d o n t Italian d ɛ n t ə * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

56 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n θ English t ʊː - θ ** Proto-Indo-European d o n t Italian d ɛ n t ə * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

57 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n θ English t ʊː - θ ** Proto-Indo-European d o n t Italian d ɛ n t ə * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

58 Similarity Similarity Sound Classes German ʦʰ aː n - * Proto-Germanic t a n d English t ʊː - θ ** Proto-Indo-European d o n t Italian d ɛ n t ə * Proto-Romance d e n t French d a - - funktionier endlich! 17 / 32

59 Sound Classes Similarity Sound Classes Correspondence Classes In sound class approaches, sounds are divided into several types and thereby distinguished in such a way that phonetic correspondences inside a type are more regular than those between different types (Dolgopolsky 1986: 35) Diachronic Similarity Similarity is not based on synchronic resemblances of sounds but on class-membership: two sounds, how dissimilar they may be from a synchronic perspective, may still belong to the same class Class membership indicates that the probability that sounds occur in a correspondence relationship in genetically related languages is considerably high 18 / 32

60 19 / 32 Sound Classes Similarity Sound Classes k g p b ʧ ʤ f v t d ʃ ʒ θ ð s z

61 19 / 32 Sound Classes Similarity Sound Classes k g p b ʧ ʤ f v t d ʃ ʒ θ ð s z

62 19 / 32 Sound Classes Similarity Sound Classes k g p b ʧ ʤ f v t d ʃ ʒ θ ð s z

63 19 / 32 Sound Classes Similarity Sound Classes K P T S

64 20 / 32 Main Ideas Working Principle Scoring

65 21 / 32 Main Ideas Working Principle Scoring A Python Library for Sequence Alignment (wwwlingulistde/lingpy) is a suite of open source Python modules for sequence comparison, and distance analyses in quantitative historical linguistics The library allows to carry out both pairwise and multiple alignments of strings encoded in IPA or X-Sampa, using different methods and algorithms, such as global (Needleman & Wunsch 1970) and local (Smith & Waterman 1981) pairwise alignments, multiple alignments based on guide trees (Feng & Doolittle 1987), profiles (Thompson et al 1994), or iteration (Barton & Sternberg 1987)

66 22 / 32 Main Ideas Main Ideas Working Principle Scoring Alignment of Sound Class Sequences In contrast to previous approaches, which base the alignment on the sequences as they are given from the input, within the sound class approach, the input strings are first converted to sound classes before they are aligned Transitions Between Sound Classes In contrast to previous sound class approaches (cf eg Turchin et al 2010), which do not allow for transitions between sound classes, this approach is based on a specific scoring function, which defines (diachronic) similarity among different sound classes

67 23 / 32 Working Principle Main Ideas Working Principle Scoring INPUT ʧɪlɐvʲɛk ʧovɛk

68 23 / 32 Working Principle Main Ideas Working Principle Scoring INPUT ʧɪlɐvʲɛk ʧovɛk TOKENIZATION ʧ, ɪ, l, ɐ, vʲ, ɛ, k ʧ, o, v, ɛ, k

69 23 / 32 Working Principle Main Ideas Working Principle Scoring INPUT ʧɪlɐvʲɛk ʧovɛk TOKENIZATION ʧ, ɪ, l, ɐ, vʲ, ɛ, k ʧ, o, v, ɛ, k CONVERSION CILAWEK COWEK

70 23 / 32 Working Principle Main Ideas Working Principle Scoring INPUT ʧɪlɐvʲɛk ʧovɛk TOKENIZATION ʧ, ɪ, l, ɐ, vʲ, ɛ, k ʧ, o, v, ɛ, k CONVERSION CILAWEK COWEK ALIGNMENT C I L A W E K C - - O W E K

71 23 / 32 Working Principle Main Ideas Working Principle Scoring INPUT ʧɪlɐvʲɛk ʧovɛk TOKENIZATION ʧ, ɪ, l, ɐ, vʲ, ɛ, k ʧ, o, v, ɛ, k CONVERSION CILAWEK COWEK ALIGNMENT C I L A W E K C - - O W E K OUTPUT ʧ ɪ l ɐ vʲ ɛ k ʧ - - o v ɛ k

72 Scoring Main Ideas Working Principle Scoring Directionality of Sound Changes One crucial characteristic of certain well-known sound changes is their directionality, ie if certain sounds change, this change will go into a certain direction and the reverse change can rarely be attested Directionality and Sound Correspondences While the nature of certain sound changes may be directional, sound correspondences do not directly reflect this directionality, and neither do scoring functions for sequence alignments, since these are not directional per definitionem, since the distance or similarity between two segments is always the same, regardless from which segment we start to compare 24 / 32

73 25 / 32 Scoring Main Ideas Working Principle Scoring Reflecting Directionality in Undirected Networks In this approach, the directionality of certain sound changes is accounted for by creating a non-metric scoring function While in a metric scoring function the distance between two segments A and B would depend on the distance of A and B to a third segment C in such a way that, according to the triangle inequality the distance from A to B could not exceed the sum of the distances from A to C and from B to C, this does not hold for the probability of those sound correspondences, which occur as a product of directional sound change

74 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

75 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

76 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

77 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

78 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

79 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

80 Scoring Main Ideas Working Principle Scoring 10 dentals affricates fricatives velars / 32

81 27 / 32 TPPSR * * * * * * * * * * * * * v o l - d e m o r t v - l a d i m i r - v a l - d e m a r - 1

82 TPPSR 28 / 32

83 TPPSR >>> from lingpycompareseqcom import Multiple 28 / 32

84 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) 28 / 32

85 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) 28 / 32

86 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk 28 / 32

87 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') 28 / 32

88 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k 28 / 32

89 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multshow_guide_tree() 28 / 32

90 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multshow_guide_tree() /-0:ʧwɔvʲɛk / \-1:ʧovɛk /-3:ʧlovʲɛk \ \-2:ʧɪlɐvʲɛk 28 / 32

91 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multshow_guide_tree() /-0:ʧwɔvʲɛk / \-1:ʧovɛk /-3:ʧlovʲɛk \ \-2:ʧɪlɐvʲɛk >>> print ', 'join([seqcls_str for seq in \ multlingpy_seqs]) 28 / 32

92 TPPSR >>> from lingpycompareseqcom import Multiple >>> mult = Multiple(['ʧwovʲɛk', 'ʧovɛk',\ 'ʧlɔvʲɛk', 'ʧɪlɐvʲɛk']) >>> print ', 'join(multipt_seqs) ʧwɔvʲɛk, ʧovɛk, ʧlovʲɛk, ʧɪlɐvʲɛk >>> multprog_align(method='sca',mode='profile') ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multshow_guide_tree() /-0:ʧwɔvʲɛk / \-1:ʧovɛk /-3:ʧlovʲɛk \ \-2:ʧɪlɐvʲɛk >>> print ', 'join([seqcls_str for seq in \ multlingpy_seqs]) CWOWEK, COWEK, CLOWEK, CILAWEK 28 / 32

93 TPPSR 29 / 32

94 >>> multflat_cluster(03,method='sca') TPPSR 29 / 32

95 >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] TPPSR 29 / 32

96 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment 29 / 32

97 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k 29 / 32

98 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() 29 / 32

99 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() / 32

100 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() >>> multprog_align(method='sca',mode='fd') \ # simple guide-tree alignment 29 / 32

101 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() >>> multprog_align(method='sca',mode='fd') \ # simple guide-tree alignment ʧ w - ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k 29 / 32

102 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() >>> multprog_align(method='sca',mode='fd') \ # simple guide-tree alignment ʧ w - ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multiterate() 29 / 32

103 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() >>> multprog_align(method='sca',mode='fd') \ # simple guide-tree alignment ʧ w - ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multiterate() Old SoP score: New SoP score: / 32

104 TPPSR >>> multflat_cluster(03,method='sca') [1, 1, 1, 1] >>> multprog_align(method='sca',mode='profile')\ # profile-based alignment ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multsum_of_pairs() >>> multprog_align(method='sca',mode='fd') \ # simple guide-tree alignment ʧ w - ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k >>> multiterate() Old SoP score: New SoP score: ʧ - w ɔ vʲ ɛ k ʧ - - o v ɛ k ʧ - l o vʲ ɛ k ʧ ɪ l ɐ vʲ ɛ k 29 / 32

105 TPPSR TPPSR IPA-Encoding of the TPPSR The Tableaux phonétiques des patois suisses romand (TPPSR, Gauchat et al 1925) is a collection of phonetic dialect data, which was digitized in an earlier research project of the Institute for Romance Languages and Literature (Heinrich Heine University Düsseldorf) The original data was converted to IPA in order make it suitable for alignment analyses using the library The dataset consists of 480 charts (480 words and phrases) which contain phonetic information for 62 dialect points Analysis within The analysis within is done via a simple terminal-based interface which takes text-files as input and outputs the results of the alignment analyses as text-files 30 / 32

106 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu 2 sɔ tɔpriː 3 isɔ tɔʤeː 5 eisəɔ tɔprei 8 sɔ pre 11 sɔ tɔpruːʦɔ 18 sɔ pre 19 sɔ tɔpre 30 ʃʊnpre 31 ʃɔñtɔprei 34 isɔ tɔpre 54 ɛsɔ tɔprɛ 55 prɛj 56 asa o tɔdkoːt 57 sɔ tɔpreː 58 asɔ tɔpreŋ Interesting Site!

107 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː isɔ tɔʤeː 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j asa o tɔdkoːt s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ -

108 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː isɔ tɔʤeː 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j asa o tɔdkoːt s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ - Taxon-ID

109 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː isɔ tɔʤeː 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j asa o tɔdkoːt s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ - Cluster-ID

110 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː isɔ tɔʤeː Singleton 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j asa o tɔdkoːt Singleton s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ - Cluster-ID Taxon-ID

111 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː - - Singleton 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j - Singleton s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ - Cluster-ID Taxon-ID

112 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː - - Boring Site! 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ - Cluster-ID Taxon-ID

113 31 / 32 TPPSR TPPSR tppsr 69,sont tout près,pressu s ɔ - t ɔ p r iː - - Interesting Site! 5 1 ei s əɔ - t ɔ p r ei s ɔ p r e s ɔ - t ɔ p r uː ʦ ɔ s ɔ p r e s ɔ - t ɔ p r e ʃ ʊ n - - p r e ʃ ɔ n t ɔ p r ei i s ɔ - t ɔ p r e ɛ s ɔ - t ɔ p r ɛ p r ɛ j s ɔ - t ɔ p r eː a s ɔ - t ɔ p r e ŋ -

114 31 / 32 TPPSR TPPSR tppsr 66,est étroite,stricta 1 ɛetrɑːt 2 ɛɛtræːtɛ 3 ɛɛtreːta 5 ɛɛtraɛːta 8 ɛɛtrɑːɛt 11 lɛɛtræːtə 19 lɛetrɑːtə 30 lɛθɛθreiti 31 lʲɛɛhriːti 34 ɛteːtraːto 55 ɛɛtræit 56 ɛɛtrɑːət 57 ɛɛtrɛt 58 jɛɛtreːt Interesting Site!

115 31 / 32 TPPSR TPPSR tppsr 66,est étroite,stricta ɛ - e t r ɑː t ɛ - ɛ t r æː t ɛ ɛ - ɛ t r eː t a ɛ - ɛ t r aɛː t a ɛ - ɛ t r ɑːɛ t l ɛ - ɛ t r æː t ə 19 1 l ɛ - e t r ɑː t ə 30 1 l ɛ θ ɛ θ r ei t i 31 1 lʲ ɛ - ɛ h r iː t i ɛ t eː t r aː t o ɛ - ɛ t r æi t ɛ - ɛ t r ɑːə t ɛ - ɛ t r ɛ t j ɛ - ɛ t r eː t -

116 31 / 32 TPPSR TPPSR tppsr 195,une feuille,folia 1 ɔñafɔlʲ 2 nafolʲɛ 3 nafɔlʲ 5 unafɔlʲə 8 ɔñafɔjə 11 ɔñafɔlʲə 19 naføðə 30 folʲe 31 fɔłe 34 nafwolʲ 55 ɔnfɔdʲ 56 ɛnfuj 57 ɛnfuj 58 ɛnfœj

117 31 / 32 TPPSR TPPSR tppsr 195,une feuille,folia 1 1 ɔ n a f - ɔ lʲ n a f - o lʲ ɛ n a f - ɔ lʲ u n a f - ɔ lʲ ə 8 1 ɔ n a f - ɔ j ə 11 1 ɔ n a f - ɔ lʲ ə n a f - ø ð ə f - o lʲ e f - ɔ ł e n a f w o lʲ ɔ n - f - ɔ dʲ ɛ n - f - u j ɛ n - f - u j ɛ n - f - œ j -

118 TPPSR Thank You for Listening! Special thanks to the German Federal Ministry of Education and Research (BMBF) for funding our research project on evolution and classification in biology, linguistics, and the history of science (EvoClass) 1 32 / 32

Sound Correspondences in the World's Languages: Online Supplementary Materials

Sound Correspondences in the World's Languages: Online Supplementary Materials Cecil H. Brown, Eric W. Holman, Søren Wichmann Language, Volume 89, Number 1, March 2013, pp. s1-s76 (Article) Published by