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Features and Sound Inventories

Workshop on Features, Segments, Tones Konstanz, 30 October-1 November, 2005. Symposium on Phonological Theory: Representations and Architecture CUNY, February 20-21, 2004. Feature-based Explanation in Phonological Inventories. Features and Sound Inventories. Nick Clements

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Features and Sound Inventories

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  1. Workshop on Features, Segments, Tones Konstanz, 30 October-1 November, 2005 Symposium on Phonological Theory: Representations and Architecture CUNY, February 20-21, 2004 Feature-based Explanation in Phonological Inventories Features and Sound Inventories Nick Clements Laboratoire de Phonétique et Phonologie, Paris E-mail: clements@idf.ext.jussieu.fr Nick Clements Laboratoire de Phonétique et Phonologie, Paris clements@idf.ext.jussieu.fr

  2. Summary Symposium on Phonological Theory: Representations and Architecture CUNY, February 20-21, 2004 • Phonological inventories are structured in terms of a number of interacting principles which operate on distinctive features, rather than segments or phonetic parameters. • Five general principles are discussed and exemplified with respect to data drawn from a large sample of segment inventories: Features and Sound Inventories Nick Clements Laboratoire de Phonétique et Phonologie, Paris E-mail: clements@idf.ext.jussieu.fr • feature bounding • feature economy • marked feature avoidance • robustness • phonological enhancement

  3. INTRODUCTION

  4. WHY DO LANGUAGES TEND TO HAVE CERTAIN SETS OF SPEECH SOUNDS AND NOT OTHERS? • A common observation: not just any set of consonants and vowels can make up a sound system. • A central finding of the earliest work in phonology was that sound systems are structured in terms of correlations defined in terms of recurrent features. (see e.g. Trubetzkoy 1939, Martinet 1955, Hockett 1955)

  5. In recent years, however, the question of inventory structure has been more vigorously debated among phoneticians than among phonologists. This work has tended to minimize the role of features. Examples: • Adaptive dispersion theory (e.g. Lindblom 1986, Lindblom & Maddieson 1988): • maximal (or sufficient) dispersion • articulatory ease • Gestural economy (Maddieson 1995): • economize gestures

  6. Work in mainstream Optimality Theory has tended to neglect inventory structure, since constraint systems evaluate individual forms rather than system-wide generalizations. • See, however, Boersma (1997), Flemming (2002) for proposals to incorporate system-level principles such as dispersion, symmetry and articulatory effort into OT. • Paul Boersma, Functional Phonology, 1988 • Edward Flemming, Auditory Representations in Phonology, 2002 These approaches, too, have sought explanation in phonetic, rather than phonological principles.

  7. ARE FEATURES NECESSARY AT ALL? • Some phonologists have concluded that phonological theory no longer requires a restrictive inventory of distinctive features but that "phonological representation can include the entire sea of predictable or freely varying phonetic detail" (Kirchner, Robert. 2001. "Phonological contrast and articulatory effort," In Linda Lombardi, ed., Segmental Phonology in Optimality Theory, p. 112.)

  8. A FEATURE-BASED APPROACH • This talk reviews a range of evidence showing that features play a central role in the structuring of sound systems. • It proposes a number of general principles stated in terms of features, and • shows that these principles make largely accurate predictions regarding the structure of speech sound inventories.

  9. FEATURE FRAMEWORK 1. A fairly conservative set of features will be sufficient for our purposes (e.g. Halle & Clements 1983, Sagey 1986) 2. For phonetic feature definitions, we assume the framework of Quantal-enhancement theory as developed by Stevens and his collaborators (e.g. Stevens 1972, 1989, 2004, Stevens & Keyser 1989, 2001)

  10. METHOD

  11. DATA BASE • Evidence is drawn primarily from the expanded UPSID data base (Maddieson & Precoda 1989). Properties: • contains 451 phoneme inventories (representing 6-7% of the world's languages) • geographically and genetically balanced • electronic database facilitates rapid searches • results can be independently verified by others

  12. PROBLEMS WITH THE UPSID DATA BASE: • inevitable genetic skewing (e.g. Niger-Congo = 55 languages, Basque = 1 language) • heterogeneity of sources, disagreements in analyses • inclusion of some allophonic details but not others (e.g. dental vs. alveolar stops, but not apical vs. laminal stops) • many coding errors To a considerable exent, these problems are alleviated by the sheer size of the sample; however, care must be taken in interpreting results (see Basbøl 1985, Maddieson 1991, Simpson 1999, Clements 2003) Statistical testing (chi square) is used here to evaluate trends.

  13. FEATURE BOUNDING

  14. FEATURE BOUNDING • Features set an upper limit on the number of sounds and contrasts that a language may employ in its lexicon and phonology. 1) Sounds: Given a set of n features, a language may have at most 2n distinctive sounds. For example, • a language using 2 features can have up to 4 sounds (22) • one using 3 features can have up to 8 sounds (23), etc.

  15. EXAMPLE: MAJOR PLACE CATEGORIES • The features [± posterior] and [± distributed] define four major place categories in coronal sounds. apico- lamino- retroflex postalveolar/ anterior anterior palatal posterior - - - - distributed - + - +

  16. 2) Contrasts • Features also set limits on the number of contrasts a language may have. • Maximum number of contrasts = (S * S-1) / 2, where S = number of sounds. • Example: • 4 sounds define 6 contrasts: (4 * 3) / 2 = 6 • Since the two binary features [± posterior] and [± distributed] define up to 4 sounds, they predict as many as 6 contrasts, and no more.

  17. ALL 6 CONTRASTS PREDICTED BY FEATURE THEORY ARE ATTESTED • contrast: example: found in e.g.: • apical anterior vs. laminal anterior apical tvs. laminal t Temne • apical anterior vs. apical posterior apical tvs. retroflex ÿYanyuwa • apical anterior vs. laminal posterior apical t vs. palatal c Arrernte • laminal anterior vs. apical posterior laminal t vs. retroflexÿArrernte • laminal anterior vs. laminal posterior laminal t vs. palatal c Hungarian • apical posterior vs. laminal posterior retroflexÿ vs. palatal c Sindhi • Moreover, no other primary coronal contrasts were discovered in either plosives or affricates in a survey of several hundred languages (Clements 1999).

  18. PHONETIC CATEGORIES ARE LESS RESTRICTIVE • Traditional phonetic theory provides 7 (or more) different place distinctions within this region ("apico-dental", "apico-alveolar", "lamino-dental", "lamino-alveolar", "palato-alveolar", "retroflex", and "palatal"). It projects as many as 21 contrasts. • Max no. soundsMax no. contrasts • Feature theory 4 6 • Traditional phonetic theory 7 21

  19. FEATURE ECONOMY

  20. Feature Economy isthe tendency to maximize feature combinations in a given system • - Clements (2003a,b) after sources in de Groot (1931), Martinet (1955, 1968) • This principle can be observed in most speech sound inventories, regardless of their size. ...

  21. A STANDARD VARIETY OF ENGLISH: 24 CONSONANTS • ph th tSh kh • b d dZ g • f T s S • v D z Z • m n N • w l r y h • [+voiced] cross-classifies all obstruents • [+continuant] doubles the number again • [+nasal] creates nasal stops at three places of articulation

  22. THE ECONOMY INDEX • Feature economy can be quantified in terms of a measure called the economy index. Given a system using F features to characterize S sounds, we can define its economy index E (to a first approximation) by the expression • E =S/F • Example: English has 24 consonants and requires a minimum of 9 features to distinguish them : • [labial], [dorsa]l, [continuant], [voiced], [glottal], [strident], [posterior], [nasal], [lateral] • The economy index of the English consonant system is therefore 24/9, or 2.7

  23. Examples: sounds features E English 24 9 2.7 English + 1 sound 25 9 2.8 English - 1 feature 24 8 3.0 • Feature Economy can now be more exactly defined as the tendency to maximize E. • This goal can be accomplished either by: • - increasing the number of sounds S, or • - decreasing the number of features F

  24. TESTING FEATURE ECONOMY • A testable prediction of feature economy is Mutual Attraction: "A given speech sound will have a higher than expected frequency in inventories in which all its features are distinctively present in other sounds." • For instance, a stop with a certain laryngeal feature L should occur more frequently in systems having other stops with the same feature L. • Let us look at an example. • …

  25. P vs. T • P vs. K • T vs. K • Ph vs. Th • Ph vs. Kh • Th vs. Kh • P’ vs. T’ • P’ vs. K’ • T’ vs. K’ • B vs. D • B vs. G • D vs. G • Bh vs. Dh • Bh vs. Gh • Dh vs. Gh • B< vs. D< • B< vs. G< • D< vs. G< COMPARISONS OF PAIRS OF STOPS SHARING MANNER FEATURES, BUT DIFFERING IN PLACE • All comparisons are positive at a high level of significance (p<.0001). That is, languages having one member of each pair tend strongly to have the other.

  26. CROSS-CATEGORY ATTRACTION Feature economy also applies across manner categories. • For example, it predicts that a language having the sounds • P T K, B D G, and F S X • will tend to also have the sounds V Z Ä, thereby maximizing the use of [+voiced] and [+continuant]. • Result (Clements 2003): • voiced labial fricatives V are much more frequent than expected in languages also having P, B, and F • analogous results hold for Z and Ä • these trends are significant at the .0001 level

  27. MARKED FEATURE AVOIDANCE

  28. in the absence of markedness, sound systems making use of n features would be expected to display the theoretical maximum of 2n sounds • no languages come close to approaching this maximum; instead, segments characterized by marked feature values tend to be avoided Markedness is understood here asthe systematic avoidance of certain widely disfavored feature values -- the marked values (Trubetzkoy 1939, Jakobson 1941, Greenberg 1968, Chomsky & Halle 1968, Kean 1980, Calabrese 1994, 2005, Rice 2002). Markedness counteracts the free operation of Feature Economy:

  29. Recall the English consonant system: ph th tSh kh b d dZ g f T s S v D z Z m n N w l r y h Absent feature combinations correspond largely to cross-linguistically disfavored consonant types

  30. At the same time, Feature Economy counteracts Markedness Example: voiced fricatives • voiced fricatives involve the marked feature values [+voiced] and [+continuant]. • voiced fricatives are absent in roughly half the world's languages. • however, due to the effect of feature economy, if a language has one voiced fricative, it is twice as likely to have another. • / . . .

  31. VOICED FRICATIVES IN UPSID • [labial] V (overall: 32.6 %) • in languages having no other voiced fricative: 13.5% • in languages having another voiced fricative: 60.3 % • [coronal] Z (overall: 38.6 %) • in languages having no other voiced fricative: 16.3 % • in languages having another voiced fricative: 73.7 % • [dorsal] Ä (overall: 15.5 %) • in languages having no other voiced fricative: 3.3 % • in languages having another voiced fricative: 29.2 %

  32. HOW DO WE KNOW WHICH VALUE OF A FEATURE IS MARKED? • Phonetic approaches • Phonetic theory involves an extremely rich set of interacting principles that frequently lead to conflicting expectations. • example: which value of [±nasal] is marked? • Statistical approaches • The likelier (more frequent, more predictable) value of a feature is its unmarked specification (Kean 1980, Hume 2004) • A statistical approach has the advantage of relating markedness to observable frequency distributions that can be readily extracted by language learners (Pierrehumbert 2003)

  33. As pointed out by Greenberg (1966) and others, markedness is reflected in frequency differences at many levels. For example, sounds bearing marked feature values tend to be less frequent: • in the lexicon • in running texts • in early stages of language acquisition • in adult sound inventories

  34. all languages have: • some lack: • marked feature value: • oral sounds • nasal sounds • [+nasal] • nonstrident sounds • strident sounds • [+stridentl] • unaspirated sounds • aspirated sounds • [spread glottis] • unglottalized sounds • glottalized sounds • [constricted glottis] • anterior sounds • posterior sounds • [+posterior] • obstruent consonants • sonorant consonants • [+sonorant] • obstruent stops • obstruent continuants • [+continuant] A PROPOSED CRITERION: MARKEDNESS AS NONUBIQUITY • A feature value is marked if it is absent in some language in classes of sounds it which it is potentially distinctive; otherwise it is unmarked. Examples:

  35. THE MARKED SUBSET PRINCIPLE (MSP) • "Within any class of sounds in which a given feature F is potentially distinctive, sounds bearing marked values of F are less frequent than sounds bearing unmarked values of F" • In other words, languages tend to avoid marked feature values, regardless of the class of sounds they occur in. • The prediction is that this principle will hold except where overridden by a competing principle.

  36. SOME PREDICTIONS OF THE MARKED SUBSET PRINCIPLE ( < is to be read “are less frequent than”) • a. in the class of vowels, nasal vowels < oral vowels (markedfeature: [+nasal]) • b. in the class of consonants, sonorants < obstruents (markedfeature: [+sonorant]) • c. in the class of obstruents, fricatives < stops (markedfeature: [+continuant]) • Do these predictions hold? Consider again English. • s

  37. Prediction (a): nasal vowels < oral vowels true (English has no nasal vowels) Prediction (b): sonorants < obstruents true (see below) • ph th tSh kh • b d dZ g • f T s S • v D z Z • m n N • w l r y h Prediction (c) : fricatives < stops false ! why ?

  38. A COMMON TYPE OF EXCEPTION TO THE MARKED SUBSET PRINCIPLE The number of marked sounds is often equal to the number of unmarked sounds. Examples: • English: fricatives = stops • Ikwere: nasal vowels = oral vowels i iâ u u) • I Iâ U U) • e e) o o) • E E)  ) • a a) In such cases, Feature Economy overrides the MSP

  39. A FURTHER PREDICTION OF THE MSP: Marked segment types usually appear in larger inventories than their unmarked counterparts. • Example (K = any dorsal stop, velar or uvular): by the MSP, • labialized ejectives Kw' should be present only if their simpler counterparts K' and Kw are also present • similarly, K' andKw should be present only if K is present • Thus, on average, • Kw' should occur in the largest inventories; • K' and Kw in the next largest inventories; • K in the smallest inventories. • ... what are the facts?

  40. FREQUENCIES IN UPSID CONFIRM THESE PREDICTIONS • sound: marked featurestotal lgs.av. no. of cons. • Kw’ 2 23 35.8 • K’ 1 68 29.0 • Kw 169 26.4 • K 0 450 19.7

  41. MARKEDNESS: SUMMARY • Marked feature values are defined as those that are not present in all languages (Nonubiquity) • Marked feature values tend to be avoided in inventories (Marked Feature Avoidance) • This tendency holds in all classes of sounds (the Marked Subset Principle), but can be overridden by other principles (Feature Economy) • Marked segment types generally appear in larger inventories than their unmarked counterparts

  42. PHONOLOGICAL ENHANCEMENT

  43. PHONOLOGICAL ENHANCEMENT • Enhancement is the name given to the reinforcement of acoustically weak feature contrasts by increasing the auditory distance between their members (Stevens, Keyser & Kawasaki 1986, Stevens & Keyser 1989, 2001). • Two forms of enhancement: • 1) phonological enhancement, in which a redundant feature is activated in the phonology to reinforce a contrast • example: [+back] vowel  [+rounded] • to reinforce the acoustic contrast with / i / 2) phonetic enhancement, in which an articulatory gesture is activated to reinforce a contrast example: the posterior fricative / / tends to be somewhat rounded in English to reinforce the acoustic contrast with /s/

  44. PHONOLOGICAL ENHANCEMENT • typically involves the activation of a marked feature value to reinforce an existing contrast. Reinforcement may take place: • A) along the same acoustic dimension: example: [+back,-low] vowel  [+rounded] acoustic dimension: F2 B) along a separate dimension: example: [coronal,+posterior] stop  [+strident] dimension 1 (posterior): lower spectral frequency of fricative noise dimension 2 (strident): higher amplitude noise

  45. ENHANCEMENT INTERACTS WITH MARKEDNESS • Enhancement creates a class of regular exceptions to the predictions of the MSP whenever the marked values which enhance a contrast become more frequent than the corresponding unmarked values. • For example, [+rounded] is the marked value of [±rounded], yet /u/ is commoner than / µ / in vowel systems with / i / • / u /, bearing the marked value [+rounded], is more frequent than its unmarked counterpart / µ /. • Here, then, Enhancement overrides Markedness.

  46. in the class of: • more frequent: • less frequent: • a. coronal stops • coronal fricatives • t [-strident] (450) • s [+strident] (397) • tS [+strident] (291) • T [-strident] (105) • b. anterior coronal stops • posterior coronal stops • t [-strident] (450) • tS [+strident] (235) • ts [+strident] (148) • c [-strident] (138) • c. vowels • obstruents • sonorants • a [-nasal] (451) • t [-nasal] (451) • n [+nasal] (445) • a) [+nasal] (102) • nt [+nasal] (57) • l [-nasal] (428) • d. labial stops • labial sonorants • labial fricatives • p [-labiodental] (446) • B [-labiodental] (34) • f [+labiodental] (199) • pf [+labiodental] (7) • V [+labiodental] (7) • ¸ [-labiodental] (82) • e. low vowels • nonlow front vowels • nonlow back vowels • a [-rounded] (448) • i [-rounded] (449) • u [+rounded] (444) •  [+rounded] (22) • y [+rounded] (33) • µ [-rounded] (62) EXAMPLES OF FEATURE ENHANCEMENT

  47. FEATURE ECONOMY INTERACTS WITH ENHANCEMENT • Redundant features used to enhance contrasts tend to be used maximally: • System A System B • i u i u • e o e  • E  E  • a a

  48. ROBUSTNESS

  49. ROBUSTNESS • Robustness is the principle according to which • features are organized in terms of a hierarchy of preference which is similar across languages, and • in the composition of sound inventories, higher-ranked features are made use of before lower-ranked features. • (Sources: Jakobson 1968, Jakobson & Halle 1956, Chomsky & Halle 1968: 409-410, Kean 1980, Stevens & Keyser 1989, Dinnsen 1992, Calabrese 1994)

  50. The idea underlying robustness is that certain feature contrasts have a higher "survival value" across time and space, and are accordingly commoner in sound inventories. • robust contrasts are, in general, those that are mastered fairly early in the process of language production -- one criterion of articulatory ease -- and that allow one sound to be easily distinguished from another, even in rapid speech and under conditions of noise • robust contrasts tend to increase the overall communicative value of a system by maximizing salience and economy at a low articulatory cost.

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