| { |
| "paper_id": "P85-1030", |
| "header": { |
| "generated_with": "S2ORC 1.0.0", |
| "date_generated": "2023-01-19T09:39:45.737468Z" |
| }, |
| "title": "Stress AJ~p,aMm is Lett~ m Se,,td Rats fer Speech Sy~", |
| "authors": [ |
| { |
| "first": "Kenneth", |
| "middle": [], |
| "last": "Church", |
| "suffix": "", |
| "affiliation": {}, |
| "email": "" |
| } |
| ], |
| "year": "", |
| "venue": null, |
| "identifiers": {}, |
| "abstract": "", |
| "pdf_parse": { |
| "paper_id": "P85-1030", |
| "_pdf_hash": "", |
| "abstract": [], |
| "body_text": [ |
| { |
| "text": "synthesizers because stress dependencies cannot be determined locally. It is impossible to determine the stress of a word by looking through a five or six character window, as many speech synthesizers do. Wellknown examples such as degrade / dbgradl, tion and tMegraph / telegraph5 demonstrate that stress dependencies can span over two and three syllables. This paper will pre~nt a principled framework for dealing with these long distance dependencies. Stress assignment will be formulated in terms of Waltz' style constraint propagation with four sources of constraints: (1) syllable weight. (2) part of speech. (3) morphology and (4) etymology. Syllable weight is perhaps the most interesting, and will be the main focus of this paper. Most of what follows has been implemented.", |
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| "sec_num": null |
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| "text": "A speech synthesizer is a machine that inputs a text stream and outputs an accoustic signal. One small piece of this problem will be discussed here: words --phonemes. The resulting phonemes are then mapped into a sequence of Ipe dyads which are combined with duration and pitch information to produce speech. text --intonation phrases --words phonemes --Ipc dyads + prosody --accousti\u00a2 -~ There are two general approaches to word --phonemes:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I. Back~e,,sd", |
| "sec_num": null |
| }, |
| { |
| "text": "\u2022 Dictionary Lookup \u2022 Letter to Sound (i.e.. sound the word out from basic principles)", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "I. Back~e,,sd", |
| "sec_num": null |
| }, |
| { |
| "text": "Both approaches have their advantages and disadvantages; the dictionary approach fails for unknown words (e.g.. proper nouns) and the letter to sound approach fails when the word doesn't follow the rules, which happens all too often in English. Most speech synthesizers adopt a hybrid strategy, using the dictionary when appropriate and letter to sound for the rest.", |
| "cite_spans": [], |
| "ref_spans": [], |
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| "section": "I. Back~e,,sd", |
| "sec_num": null |
| }, |
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| "text": "Some people have suggested to me that modern speech synthesizers should do away with letter to sound rules now that memory prices are dropping so low that it ought to be practical these days to put every word of English into a tiny box. Actually memory prices are still a major factor in the cost of a machine. But more seriously, it is not possible to completely do away with letter to sound rules because it is not possible to enumerate all of the words of English. A typical college dictionary of 50,000 hcadwords will account for about 93% of a typical newspaper text. The bulk of the unknown words are proper flOUfl-q.", |
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| "eq_spans": [], |
| "section": "I. Back~e,,sd", |
| "sec_num": null |
| }, |
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| "text": "The difficulty with pmpor nouns h demonstrated by the table below which compares the Brown Corpus with the surnames in the Kansas City Telephone Book. The table answers the question: how much of each corpus would be covered by a dictionary of n words? Thus the first line shows that a dictionary of 2000 words would cover 68% of the Brown Corpus, and a dictionary of 2000 names would cover only 46% of the Kansas City Telephone Book. It should be clear from the table that a dictionary of surnames must be much targar than a typical college dictionary ('20,000 entries). Moreover. it would be a lot of work to consu'u~ such a dictionary since there are no existing computer readable dictionaries for surnames. Brown Size of Word Dictionary Corpus Name Diczionary 2000 68% 2000 4000 78% 4000 6000 83% 6000 8000 86% 8000 lO000 89% 10000 12000 91% 12000 14000 92% 14000 16000 94% 16ooo ! 800O 95% 18000 20000 95% 20000 22000 96% 22000 24000 97% 24000 26000 97% 26000 28000 98% 28000 30000 98% 30000 32000 98% 32000 34000 99% 34000 36000 99% 36000 38000 99% 38000 40(3O0 99% Kansas 46% 57% 63% 68% 72% 75% 77% 79% 81% 83% 84% 86% 87% 88% 89% 9O% 91% 91% 92% 93% Actually, this table overestimates the effectivene~ of the dictionary, for practical applications. A fair test would not use the same corpus for both selecting the words to go into the dictionary and for testing the coverage. The scores reported here were computed post hoc, a classic statistical error, l tried a more fair test, where a dictionary of 43777 words (the entire Brown Corpus) was tested against a corpus of 10687 words selected from the AP news wire. The results showed 96% coverage, which is slightly lower (as expected) than the 99% figure reported in the table for a 40000 dictionary.", |
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| "ref_spans": [ |
| { |
| "start": 710, |
| "end": 1394, |
| "text": "Brown Size of Word Dictionary Corpus Name Diczionary 2000 68% 2000 4000 78% 4000 6000 83% 6000 8000 86% 8000 lO000 89% 10000 12000 91% 12000 14000 92% 14000 16000 94% 16ooo ! 800O 95% 18000 20000 95% 20000 22000 96% 22000 24000 97% 24000 26000 97% 26000 28000 98% 28000 30000 98% 30000 32000 98% 32000 34000 99% 34000 36000 99% 36000 38000 99% 38000 40(3O0 99% Kansas 46% 57% 63% 68% 72% 75% 77% 79% 81% 83% 84% 86% 87% 88% 89% 9O% 91% 91% 92% 93% Actually, this table overestimates the effectivene~ of the dictionary, for practical applications. A fair test would not use the same corpus", |
| "ref_id": null |
| } |
| ], |
| "eq_spans": [], |
| "section": "I. Back~e,,sd", |
| "sec_num": null |
| }, |
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| "text": "For names, the facts are much more striking as demonstrated in the following Note that the asymptote of 60% coverage is quickly reached after only about 5000-1000 words, su88estiog (a) that the dictionary appnxtch may only be suitable for the 5000 to 1000 mint frequent names because larger dictionaries yield only negligible improvements in performance, and (b) that the dictionary approach has an inherent limitation on coverage of about 60%. To increase the coverage beyond this, it is probably neceqsary to apply alternative methods such as letter to sound rules.", |
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| "section": "Size of", |
| "sec_num": null |
| }, |
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| "text": "Over the past year l have been developing a set of letter to sound rules as part of a larger speech synthesis project currently underway at Murray Hill. Only one small piece of my letter to sound rules, orthography ~ stress, will be discussed here. The output streu assignment is then used to condition a number of rules such as palatalization in the mapping from letters to phonemes.", |
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| "section": "Size of", |
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| "text": "Intuitively, stre~s dependencies come in two flavors: (a) those that apply locally within a syllable, and (b) throe that apply globally between syllables. Syllable weight is an attempt to represent the local stress constraints. Syllables are marked either heavy or light, depending only on the local 'shape' (e.g., vowel length and number of Ix~t-vocalic consonants). Heavy syllables are more likely to be", |
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| "eq_spans": [], |
| "section": "we/ght as ~ i,termt~tm ~ of Relm~mmutm", |
| "sec_num": "2." |
| }, |
| { |
| "text": "\u2022 Admittedly. this teat is somewhat unfair to the dictionary appma\u00a9h sinca: thu ethnic mzxture in gamuut City is very differeat from that found here at Bell t.aboflltot~ stressed than light syllables, though the actual outcome depends upon contextual constraints, such as the English main stress rule, which will be d~ shortly. ", |
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| "section": "we/ght as ~ i,termt~tm ~ of Relm~mmutm", |
| "sec_num": "2." |
| }, |
| { |
| "text": "Recall that Waltz was the first to showed how contraints could be used effectively in his program that analyzed line drawings in order to separate the figure from the ground and to distinguish concave edges from convex ones. He first assigned each line a convex label (+), a concave label (-) or a boundary label (<, >), using only ~ocal information. If the local information was ambiguous, he would assign a line two or more labels. Waltz then took advantage of the constraints impmed where multiple lines come together at a common vertex. One would think th~ t there ought to be 42 ways to label a vertex of two lines and 4 '~ ways to label a vertex of three lines and so on. By this argument, there ought to be 208 ways to label a vertex. But Waltz noted that there were only 18 vetex labelings that were consistent with certain reasonable assumptions about the physical world. Because the inventory of possible labelings was so small, he could disambiguate lines with multiple assignments by checking the junctures at each end of the line to see which of the assignments were consistent with one of the 18 possible junctures. This simple test turned out to be extremely powerful. The strength of these constraints will help make up for the fact that the mapping from orthography to weight is usually underdetermined, In terms of information theory, about half of the bits in the weight representation arc redundant since log 51 is about half of log 1020.", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "This means that I only have to determine the weight for about half of the syllables in a word in order to assign stress. For practical purposes, Sproat's table offers a complete solution to the weight --stress subtask. All that remains to be solved is: orthography weight. Unfortunately, this problem is much more dif~cult and much less well understood. 1'11 start by discussing some easy _~_,-e~, and then introduce the pseudo-weight heuristic which helps in some o[ the more di~icuit cas~. Fortunately, l don't need a complete solution to orthography ~ weight since weight ~ stress is so well constrained.", |
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| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "In easy cases, it is pmsible m determine the weight directly for the orthography. For example, the weight of torment must be \"HH\" because both syllables arc cloud (even after stripping off the final consonant). Thus, the stress of torment is either \"31\" or \"13\" stress depending on whether is has 0 or I extrametricai final syllables:\" (strop-from-weights \"HH\" 0) --('31\")", |
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| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "; verb (stress-from-weights \"HH\" l) --('13\")", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "; noun However, meet cases are not this easy. Consider a word like record where the first syllable might be light if the first vowel is reduced or it might be heavy if the vowel is underlyingly long or if the first syllable includes the /k/. It seems like it is imix~sstble to say anything in a case like this. The weight, it appears is either \"LH\" or \"HH'. Even with this ambiguity, there are only three distinct stress assignments: 01, 31, and 13.", |
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| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "AaueUy, ~ practk~. ~ ~l~t det~mm~on is ~mp~aud by t0,,, Smm~5~ -crazy ted -ew m, lht be mmx~. New, for example, ths| the tdj~:tiw ~ den ~ m'~/ike the '.~ mrm~w bin:sum Uul sdjm:trmd e~ .~w ie mumuneuncaL (stress-from-weights \"LH\" 0) --('01 \") (strm.(rom.weights \"HH\" 0) --('31\") (sirra-from-weights \"LH\" I) --('13\") (streas-from-weights \"HH\" l) --('13\")", |
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| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "8. Pmdee-Wekdn", |
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| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "In fact. it is possible now to use the stress to further constrain the weight. Note that if the first syllable of record is light it must also be unstressed and if it is heavy it also must be stressed. Thus, the third line above is inconsistent.", |
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| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "I implement this additional constraint by assigning record a pseudoweight of \"'-H', where the \"-.\" sign indicates that the weight a~sigment is constrained to be the same as the stress assigment (either heavy & stressed or not heavy & not stressed), [ can now determine the possible stress assignments of the p~eudo-weight \".-H\" by filling in the \"\"\" constraint with all possible bindings (H or L) and testing the results to make sure the constraint is met.", |
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| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "(strew-from-weights \"LH\" 0) --('I)1 \") (stress-from-weights \"HH\" 0) --('31 \") (stress-from-weights \"LH\" I) --('13\") ; No Good", |
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| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "(stress-from-weights \"HH\" l) --('13\")", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "Of the four logical inputs, the --constraint excludes the third case which would assign the first syllable a stress but not a heavy weight. All three of these possibilities are grammatical.", |
| "cite_spans": [], |
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| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "The following pseudo-weights are defined: [ have already given examples of the labels H, L and -. S and R are used in certain morphological analyses (see below), N is used for examples where Hayes would invoke his rule of Sonorant Destr-~ing (see below), and ? is not used except for demonstrating the program.", |
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| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
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| "text": "The procedure that assigns pseudo-weight to orthography is roughly as outlined below, ignoring morphology, etymological and more special cases than [ wish to admit. assignments meeting all of the constraints. After analyzing over 20.000 words, there were no more than 4 possible stress assigments for any particular combinatton of pseudo-weight and number of extrametrical number of syllables. Most observed combinations had a unique stre~ assignment, and the average (by observed combination with no frequency normalization) has 1.5 solutions. In short, the constraints are extremely powerful; words like record with multiple stress patterns are the exception rather than the rule.", |
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| "section": "Amlolff with Walt-' Comtndat Prolmptiea Paradigm", |
| "sec_num": "6." |
| }, |
| { |
| "text": "Generally, when there are multiple stress assignments, one of the possible stress assigments is much more plausible than the others. For instance, nouns with the pseudo-weight of \"H--L* (e.g., difference)", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "have a strong tendency toward antipenultimate stress, even though they could have either 100 or 310 stress depending on the weight of the penultimate. The program takes advantage of this fact by returning a sorted list of solutions, all of which meet the constraints, but the solutions toward the front of the list are deemed more plausible than the solutions toward the rear of the list.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "(stress-from-weights \"l-I--L\" I) --('100\" \"3 I0\")", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Sorting the solution space in this way could be thought of as a kind of default reasoning mechanism. That is, the ordering criterion, in effect, assigns the penultimate syllable a default weight of L. unless there is positive evidence to the contrary. Of course, this sorting technique is not as general as an arbitrary default reasoner, but it seems to be general enough for the application. This limited defaulting mechanism is extremely efficient when there are only a few solutions meeting the constraints.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "This default mechanism is also used to stress the following nouns According to what has been said so far, these sonorant syllables are closed and so the penultimate syllable should be heavy and should therefore be stressed. Of course, these nouns all have antipenultimate stress, so the rules need to be modified. Hayes suggested a Sonorant Dnstressing rule which produced the desired results by erasing the foot structure (destressing) over the penultimate syllable so that later rules will reanalyze the syllable as unstressed. I propose instead to assign these sonorant syllables the pseudo-weight of N which is essentially identical to -.* In this way. all of these words will have the pseudoweight of HNH which is most likely stressed as 103 (the correct answer) even though 313 also meets the constraints, but fair worse on the ordering criteron.", |
| "cite_spans": [], |
| "ref_spans": [], |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "(stress-from-weights \"HNH\" I) --('I03\" \"313\")", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "Contrast the examples above with Adirondack where the stress does not back ap past the sonorant syllable. The ordering criterion is adjusted to produce the desired results in this case, by assuming that two binary feet (i.e., 2010 stress) are more plausible than one tertiary foot (i.e., 0100 stress).", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "(weights-from-orthography \"Adirondack') --\"L-NH\" (stress-from-weights \"L-NH') --('2013\" \"0103\") It ought to be possible to adjust the ordering criterion in this way to produce (essentially) the same results as Hayes\" rules.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "tO. M~ Thus far, the di~-usion has assumed monomorphemic input. Morphological affixes add yet another rich set of constraints. Recall the examples mentioned in the abstract, degrhde/dlrgrudhtion and tklegruphkei~grophy, which were used to illustrate that stress alternations are conditioned by morphology. This section will discuss how this is handled in the program. The task is divided into two questions: (I) how to parse the word into morphemes, and (2) how to integrate the morphological parse into the rest of stress assignment procedure discussed above. ~\" N s-d -used to I~ idlm\"aL I sm -,ill am mm du~ differeeczs us just~'=d. At in,/tram. IU differt~s m~l vm7 ml~ t-aad \u00a2~rtamly om ~q)rth pin S into h~e.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| { |
| "text": "The morphological parser uses a grammar roughly of the form:", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "word --level3 (regular-inflection)* level3 --(level3-prefix) * level2 (level3-suffix)* level2 --(levei2-prefix)* levell (level2-suffix)* levell ~ (levell-profix)* (syl)* (leveli-suffix)*", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| { |
| "text": "where latinate affixes such as in+. it+, ac+, +ity, +ion. +ire. - \u2022 Level I Phonological Rules: Quite a number of phonological rules apply at level I but not at level 2. For instance, the so-called trio syllabic will lax a vowel before a level I suffix (e.g.. divine --divin+ity) but not before a level 2 suffix (e.g., dcvine#ly and devine#hess). Similarly, the role that maps /t/ into /sd in president ~ pre~dency also fails to apply before a level 2 affix: president#hood (not *presidence#hood).", |
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| { |
| "start": 36, |
| "end": 65, |
| "text": "it+, ac+, +ity, +ion. +ire. -", |
| "ref_id": null |
| } |
| ], |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Given evidence such as this, there can be little doubt on the necessity of the level ordering distinction. Level 2 affixes are fairly easy to implement; the parser simply strips off the stress neutral affixes, assigns stress to the parts and then pastes the results back together.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "For instance, paremhood is parsed into parent and #hood. The pieces are assigned 10 and 3 stress respectively, producing 103 stress when the pieces are recombined. In general, the parsing of level 2 affixes is not very. difficult, though there are some cases where it is very difficult to distinguish between a level I and !evel 2 affix. For example, -able is level 2 in changeable (because of silent \u2022 which is not found before level I suffixes), but level I in cbmparable (bocause of the strees shift from compare which is not found before level 2 suffixes). For dealing with a limited number of affixes like .able and -merit, there are a number of special purpose diagnnstic procedures which decide the appropriate level.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "Level I suffixes have to be strer,,sed differently. In the lexicon, each level I suffix is marked with a weight. Thus, for example, the su~ +~'ty is marked RR. These weights are assigned to the last two syllables, regularless of what would normally be computed. Thus, the word civii+ity is assigned the pseudo-weight ---RR which is then assigned the correct stress by the usual methods:", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "(stress-from-weights \"'--RR\" 1) --('0100\" \"3100\")", |
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| "ref_spans": [], |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| { |
| "text": "The fact that +ity is marked for weight in this way makes it relatively easy for the program to determine the location of the primary stress. These selected results are biased slightly in favor of the program.", |
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| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
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| "text": "Over all, the program correctly assigns primary stress to 82% of the words in the dictionary, and 85% for words ending with a level I affix. Fujimhki. Fujim&o. Fujim;,ru. Funasl, ka, Toybta. Um~da. One might expect that a loan word would be stressed using either the rules of the the language that it was borrowed from or the rules of the language that it was borrowed into. But neither the rules of Japanese nor the rules of English can account for the penultimate stress in Japanese loans.", |
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| "start": 141, |
| "end": 197, |
| "text": "Fujimhki. Fujim&o. Fujim;,ru. Funasl, ka, Toybta. Um~da.", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "I believe that speakers of English adopt what i like m call a pseudoforeign accent. That is. when speakers want to communciate that a word is non-native, they modify certain parameters of the English stress rules in simple ways that produce bizarre \"foreign sounding\" outputs. Thus, if an English speaker wants to indicate that a word is Japanese, he might adopt a pseudo-Japanese accent that marks all syllables heavy regnardless of their shape. Thus, Fujimfira, on this account, would be assigned penultimate stress because it is noun and the penultimate syllable is heavy. Of course there are numerous alternative pseudo-Japanese accents that also produce the observed penultimate stress. The current version of the program assumes that Japanese loans have light syllables and no extrametricality. At the present time, I have no arguments for deciding between these two alternative pseudo-Japanese accents.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "The pseudo-accent approach presupposes that there is a method for distinguishing native from non-native words, and for identifying the etymological distinctions required for selecting the appropriate pseudo-accent. Ideally, this decision would make use of a number of phonotactic and morphological cues, such as the fact that Japanese has extremely restricted inventory of syllables and that Germanic makes heavy use of morphemes such as .berg, wein. and .stein.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Unfortunately, because I haven't had the time to develop the right model, the relavant etymological distinctions are currently decided by a statistical tri-gram model. Using a number of training sets (gathered from the telephone book, computer readable dictionaries, bibliographies, and so forth), one for each etymological distinction. I estimated a probability P(xyz~e) that each three letter sequence xyz is associated with etymology e. Then. when the program sees a new word w, a straightforward Baysian argument is applied in order to estimate for each etymology a probability P(eb*) based on the three letter sequences in w.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "I have only just begun to collect training sets, but already the results appear promising. Probability estimates are shown in the figure below for some common names whose etymology most readers probably know. The current set of etymologies are: Old French (OF ME) . Latin (L). Gaelic (NBrit). French (Fr). Core (Core). Swedish (Swed). Ru~lan (Rus). Japanese (Jap). Germanic (Get), and Southern Romance (SRom). Only the top two candidates are shown and only if the probability estimate is 0.05 or better.", |
| "cite_spans": [ |
| { |
| "start": 260, |
| "end": 263, |
| "text": "ME)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "As is to be expected, the model is relatively good at fitting the training data. For example, the following names selected from the training data where run through the model and assigned the label Jap with probability 1.00: Fujimaki, Fujimoto. Fujimura. Fujino. Fujioka. Fujisaki. Fujita, Fujiwara. Fukada. Fukm'. Fukanaga. Fukano. Fukase. Fukuchi. Fukuda. Fukuhara. Fukui. Fukuoka. FukusMma. Fukutake. Funokubo, Funosaka. Of 1238 names on the Japanese training list, only 48 are incorrectly identified by the model: Abe.", |
| "cite_spans": [ |
| { |
| "start": 224, |
| "end": 422, |
| "text": "Fujimaki, Fujimoto. Fujimura. Fujino. Fujioka. Fujisaki. Fujita, Fujiwara. Fukada. Fukm'. Fukanaga. Fukano. Fukase. Fukuchi. Fukuda. Fukuhara. Fukui. Fukuoka. FukusMma. Fukutake. Funokubo, Funosaka.", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Amemiya. Ando. Aya. Baba. Banno. Chino. Denda. Doke. Oamo. Hose. Huke. id\u00a2. lse. Kume. ICuze. Mano. Maruko. Marumo. Mosuko. Mine. Musha. Mutai. Nose. Onoe. Ooe, Osa. Ose. Rai. Sano. gone. Tabe. Tako. Tarucha. Uo. Utena. Wada and Yawata. As these exceptions demonstrate, the model has relatively more difficulty with short names, for the obvious reason that short names have fewer trigrams to base the decision on. Perhaps short names should be dealt with in some other way (e.g.. an exception dictionary). I expect the model to improve as the training sets are enlarged. It is not out of the question that it might be possible to train the model on a very large number of names, so that there is a relatively small probability that the program will be asked to estimate the etymology of a name that was not in one of the training sets. If. for example, the training sets included the I00OO must frequent names, then mint of the names the program would be asked about would probably be in one the training sets (assuming that the results reported above for the telephone directories also apply here).", |
| "cite_spans": [ |
| { |
| "start": 9, |
| "end": 224, |
| "text": "Ando. Aya. Baba. Banno. Chino. Denda. Doke. Oamo. Hose. Huke. id\u00a2. lse. Kume. ICuze. Mano. Maruko. Marumo. Mosuko. Mine. Musha. Mutai. Nose. Onoe. Ooe, Osa. Ose. Rai. Sano. gone. Tabe. Tako. Tarucha. Uo. Utena. Wada", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Before concluding. I would like to point out that etymology is not just used for stress assignment. Note. for instance, that orthographic ch and gh are hard in Italian loans Macchi and spaghetti, in constrast to the general pattern where ch is /ch/ and /ghJ is silent. In general. velar softening seems to be cooditionalized by etymology. Thus, for er, ample\" /g/ is usually soft before /I/ (as in ginger) but not in girl and Gibson and many other Germanic words. Similarly. other phonological rules (especially vowel shift) seem to be conditionalized by etymology. [ hope to include these topics in a longer version of this paper to be written this summer.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Order~ Muitipte Selmime", |
| "sec_num": "9." |
| }, |
| { |
| "text": "Stress assignment was formulated in terms of Waltz' constraint propagation paradigm, where syllable weight played the role of Waltz' \u2022 labels and Sproat's weight table played the role of Waltz' vertex constraints. It was argued that this formalism provided a clean computational framework for dealing with the following four linguistic issues:", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Cmc~l~t Remarks", |
| "sec_num": "12." |
| }, |
| { |
| "text": "\u2022 Syllable Weight:. oh@ /deviffop * Part of Speech:. t~rment (n) / torment (v) \u2022 Me~. degrhde /dbgradhtion", |
| "cite_spans": [ |
| { |
| "start": 75, |
| "end": 78, |
| "text": "(v)", |
| "ref_id": null |
| } |
| ], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Cmc~l~t Remarks", |
| "sec_num": "12." |
| }, |
| { |
| "text": "\u2022 Etymo/o~: c/'lculi I tortbni", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Cmc~l~t Remarks", |
| "sec_num": "12." |
| }, |
| { |
| "text": "Currently. the program correctly assigns primary streets to 82% of the words in the diotionary.", |
| "cite_spans": [], |
| "ref_spans": [], |
| "eq_spans": [], |
| "section": "Cmc~l~t Remarks", |
| "sec_num": "12." |
| } |
| ], |
| "back_matter": [], |
| "bib_entries": { |
| "BIBREF0": { |
| "ref_id": "b0", |
| "title": "The Sound Pattern of English", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [ |
| "N" |
| ], |
| "last": "Chomsky", |
| "suffix": "" |
| }, |
| { |
| "first": "M", |
| "middle": [], |
| "last": "Halle", |
| "suffix": "" |
| } |
| ], |
| "year": 1968, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Chomsky. N.. and Halle, M., The Sound Pattern of English. Harper and Row, 1968.", |
| "links": null |
| }, |
| "BIBREF1": { |
| "ref_id": "b1", |
| "title": "A Metrical Theory of Stress Rules", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [ |
| "B P" |
| ], |
| "last": "Hayes", |
| "suffix": "" |
| } |
| ], |
| "year": 1980, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Hayes. B. P., A Metrical Theory of Stress Rules, unpublished Ph.D. thesis, MIT. Cambridge. MA., 1980.", |
| "links": null |
| }, |
| "BIBREF2": { |
| "ref_id": "b2", |
| "title": "On Stress and Linguistic Rhythm, Linguistic inquiry 8", |
| "authors": [ |
| { |
| "first": "L", |
| "middle": [], |
| "last": "Liberman", |
| "suffix": "" |
| }, |
| { |
| "first": "A", |
| "middle": [], |
| "last": "Prince", |
| "suffix": "" |
| } |
| ], |
| "year": 1977, |
| "venue": "", |
| "volume": "", |
| "issue": "", |
| "pages": "249--336", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Liberman, L., and Prince, A.. On Stress and Linguistic Rhythm, Linguistic inquiry 8, pp. 249-336, 1977.", |
| "links": null |
| }, |
| "BIBREF3": { |
| "ref_id": "b3", |
| "title": "MIT Doctoral Dissertation. available for the Indiana University Linguistics Club", |
| "authors": [ |
| { |
| "first": "", |
| "middle": [ |
| "K" |
| ], |
| "last": "Mohanan", |
| "suffix": "" |
| }, |
| { |
| "first": "", |
| "middle": [], |
| "last": "Phonology", |
| "suffix": "" |
| } |
| ], |
| "year": 1982, |
| "venue": "The Psychology of Computer Vision", |
| "volume": "", |
| "issue": "", |
| "pages": "", |
| "other_ids": {}, |
| "num": null, |
| "urls": [], |
| "raw_text": "Mohanan. K., lacxical Phonology, MIT Doctoral Dissertation. available for the Indiana University Linguistics Club. 1982. Waltz. D., Understanding Line Drawings of Scences with Shadows. in P. Winston (ed.) The Psychology of Computer Vision, McGraw-Hill.", |
| "links": null |
| } |
| }, |
| "ref_entries": { |
| "FIGREF0": { |
| "text": "H; stress is unknown weight --L; stress is unknown(weight -H) ~ (stress -O) weight -H; stress ~ 0 weight -L: stress -0 (weight -H) =~ (stress -0) weight is unknown: stress is unknownThe eoun should ~mbebly have the mm tO rtt~. tMm d~ nress [3. t u~ that te exmtmaCricef syllabk Ms 3 ~eus if it is buy% and 0 Irns if it is UZ,~t. l\"~e ~es8 of tM estrsme~L-sJ 8ylhd~hr is ~ diR'lcz~t ~ is.edict, as dilc~Jsetd ~ou].", |
| "type_str": "figure", |
| "uris": null, |
| "num": null |
| }, |
| "TABREF0": { |
| "text": "table which teats name lists of various sizes against the Bell Laboratories phone book. (As above, the name lists were gathered from the Kansas City Telephone Book.)*", |
| "type_str": "table", |
| "content": "<table><tr><td>Size of Word List</td><td>Coverage of Test Corpus</td></tr><tr><td>(Kansas)</td><td>(Befl Labs)</td></tr><tr><td>2000</td><td>0.496</td></tr><tr><td>400O</td><td>0.543</td></tr><tr><td>60OO</td><td>0.562</td></tr><tr><td>8000</td><td>0.571</td></tr><tr><td>I0000</td><td>0.577</td></tr><tr><td>20000</td><td>0.589</td></tr><tr><td>4000O</td><td>0.595</td></tr><tr><td>50000</td><td>0.596</td></tr><tr><td>6000O</td><td>0.596</td></tr><tr><td>9OOOO</td><td>0.597</td></tr></table>", |
| "html": null, |
| "num": null |
| }, |
| "TABREF1": { |
| "text": "Thus monomorphemic adjectives such as diacr~et, robfist and cbmmon stress just like verbs (the final syllable is stressed if it is heavy and otherwise the penultimate syllable is stress) whereas adjectives with single syllable suffixes such as -al, -oas. -ant, -ent and -ire follow the same pattern as regular nouns[Hayes, p. 242].", |
| "type_str": "table", |
| "content": "<table><tr><td colspan=\"4\">Adjectives stress just like verbs except suffixes are ignored</td></tr><tr><td colspan=\"4\">(extrametrical). Stress Pattera of Suffixed Adjectives</td><td>The notion of weight is derived from Chomsky and Halle's notion of strong and weak clusters [Chonuky and Halle] (SPE). In phonological theory, weight is used as an intermediate level of representation between the input underlying phonological representation and the output stress aaignment. In a similar fashion, [ will use weight as an intermediate level of representation between the</td></tr><tr><td colspan=\"2\">Light Penultimate</td><td>Hury Peaaidmate</td><td>Heavy Pmultimale</td><td>input orthography and the output strew. The orthography --stress</td></tr><tr><td colspan=\"2\">municipal</td><td>adjectival</td><td>frat&'nai</td><td>problem will be split into two subproblems:</td></tr><tr><td colspan=\"2\">magn~minous</td><td>desirous</td><td>trem~ndoas</td></tr><tr><td colspan=\"2\">significant</td><td>clairv6yant</td><td>relfictant</td><td>\u2022 Orthography --Weight</td></tr><tr><td colspan=\"2\">innocent</td><td>complY, cent</td><td>dep6'ndent</td><td>\u2022 Weight ~ Stress</td></tr><tr><td colspan=\"2\">primitive</td><td>condficive</td><td>exp~-nsive</td></tr><tr><td/><td/><td/><td/><td>3. What is Sy~</td><td>Weight:</td></tr><tr><td/><td/><td/><td/><td>Weight is a binary feature (Heavy or Light) assigned to each syllable.</td></tr><tr><td/><td/><td/><td/><td>The final syllables of the verbs obey, maintain, erase, torment.</td></tr><tr><td/><td/><td/><td/><td>collapse, and exhaust arc heavy because they end in a long vowel or</td></tr><tr><td/><td/><td/><td/><td>two consonants, in constrast, the final syllables of develop, astonish.</td></tr><tr><td/><td/><td/><td/><td>edit. consider, and promise are light because they end in a short vowel</td></tr><tr><td/><td/><td/><td/><td>and at moat one consonant. More precisely, to compute the weight of</td></tr><tr><td/><td/><td/><td/><td>a syllable from the underlying phonological representation, strip off. the</td></tr><tr><td/><td/><td/><td/><td>final consonant and then pane the word into syllables (assigning</td></tr><tr><td>pattern.</td><td/><td/><td/><td>\u00a2omommts to the right when there is ambiguity).</td></tr><tr><td colspan=\"3\">Sweat's Weight Table Part of Speech Weight Verb Noun</td><td/><td>owK\u2022y tor-men</td><td>Weight heavy final syllable heavy final syllable</td><td>Rea.~oa long vowel closed syllable</td></tr><tr><td/><td/><td/><td/><td>diy-ve-lo</td><td>light final syllable</td><td>open syllable & short vowel</td></tr><tr><td>H</td><td>.I</td><td>I</td><td/></tr><tr><td>L</td><td>l</td><td>I</td><td/><td>Then. if the syllable is clo~ (i.e., ends in a consonant as in tor.men)</td></tr><tr><td>HH</td><td>31</td><td>I0</td><td/><td>or if the vowel is marked underiyingly long (as in ow.bey), the syllable</td></tr><tr><td>HL</td><td>I0</td><td>I0</td><td/><td>is marked heavy. Otherwise, the syllable ends in an open short vowel</td></tr><tr><td>LH</td><td>01</td><td>I0 1</td><td/><td>and it is marked light. Determining syllable weight from the</td></tr><tr><td>LL</td><td>I0 I</td><td>I0 1</td><td/><td>orthography is considerably more difficult than from the underlying</td></tr><tr><td>HHH</td><td>103 ]</td><td>3101</td><td/><td>phonological form. I will return to this question shortly.</td></tr><tr><td>HHL</td><td>310 I</td><td>310</td><td/></tr><tr><td>HLH</td><td>103</td><td>1(30</td><td/><td>4. we/slt --Stnm</td></tr><tr><td>HLL</td><td>310</td><td>10O</td><td/></tr><tr><td>LHH</td><td>103</td><td>010</td><td/><td>Global stress assignment rules apply off\" the weight representation. For</td></tr><tr><td>LHL</td><td>010</td><td>010</td><td/><td>example, the main stress rule of English says that verbs have final</td></tr><tr><td>LLH</td><td>I03</td><td>10O</td><td/><td>stress if the final syllable is heavy syllable (e.g., obey), and penultimate</td></tr><tr><td>LLL</td><td>010</td><td>100</td><td/><td>stress if the final syllable light syllable (e.g., develop). The main stress</td></tr><tr><td>etc.</td><td/><td/><td/><td>rule works similarly for nouns, except that the final syllable is ignored</td></tr><tr><td/><td/><td/><td/><td>(extrametrical [Hayes]). Thus, nouns have penultimate stress if the</td></tr><tr><td/><td/><td/><td/><td>penultimate syllable is heavy (e.g, aroma) and antipenultimate stress</td></tr><tr><td/><td/><td/><td/><td>if the penultimate syllable is light (e.g., cinema).</td></tr><tr><td/><td/><td/><td/><td>\u00a3x~l~</td><td>Pesmilimte Wei~lst</td><td>R~</td></tr><tr><td/><td/><td/><td/><td>heavy</td><td>long vowel</td></tr><tr><td/><td/><td/><td/><td>verr6nda</td><td>heavy</td><td>closed syllable</td></tr><tr><td/><td/><td/><td/><td>cinema</td><td>light</td><td>open syllabic & short vowel</td></tr></table>", |
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| "num": null |
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| "TABREF2": { |
| "text": "Similarly, in this application there are very strong grammatical constraints. According to Spmat's table, there are only 51 distinct output stress a.udgnmeats, a very small number considering that there are 1020 distinct inputs.", |
| "type_str": "table", |
| "content": "<table><tr><td/><td/><td colspan=\"3\">Pe~ible Stress Assignments</td><td/></tr><tr><td>I</td><td>103</td><td>3103</td><td>020100</td><td>0202013</td><td>20020100</td></tr><tr><td>3</td><td>310</td><td>02010</td><td>020103</td><td>2002010</td><td>20020103</td></tr><tr><td>0l</td><td>313</td><td>02013</td><td>200100</td><td>2002013</td><td>20202010</td></tr><tr><td>31</td><td>010O</td><td>20010</td><td>200103</td><td>2020100</td><td>20202013</td></tr><tr><td>I0</td><td>0103</td><td>20013</td><td>202010</td><td>2020103</td><td>32020100</td></tr><tr><td>13</td><td>2001</td><td>20100</td><td>202013</td><td>3202010</td><td>32020103</td></tr><tr><td>010</td><td>2010</td><td>20103</td><td>320100</td><td>3202013</td><td/></tr><tr><td>013</td><td>2013</td><td>32010</td><td>320103</td><td>02020100</td><td/></tr><tr><td>100</td><td>3100</td><td>32013</td><td>0202010</td><td>02020103</td><td/></tr></table>", |
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| "num": null |
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| "TABREF3": { |
| "text": "The redundancy of the weight representation can also been seen directly from Sproat's weight table as shown below For a one syllable noun, the weight is irrelevant. For a two syllable noun, the weight of the penultimate is irrelevant. For a three syllable noun, the weight of the antipenultimate syllable is irrelevant if the penultimate is light.For a four syllable noun, the weight of the antipenultimate is irrelevant if the penultimate is light and the weight of the initial two syllables are irrelevant if the penultimate is heavy. These redundancies follow, of course, from general phonological prin~ples of stresa assignment.Weigi~ by Stress (fee short Noum)", |
| "type_str": "table", |
| "content": "<table><tr><td>Stress</td><td/><td colspan=\"2\">Weight</td><td/></tr><tr><td>!</td><td>L</td><td>H</td><td/><td/></tr><tr><td>lO</td><td>LL</td><td>HL</td><td/><td/></tr><tr><td>13</td><td>LH</td><td>HH</td><td/><td/></tr><tr><td>010</td><td>LHL</td><td/><td/><td/></tr><tr><td>310</td><td>HHL</td><td/><td/><td/></tr><tr><td>013</td><td>LHH</td><td/><td/><td/></tr><tr><td>313</td><td>HHH</td><td/><td/><td/></tr><tr><td>100</td><td>HLL</td><td>LLL</td><td/><td/></tr><tr><td>103</td><td>LLH</td><td>HLH</td><td/><td/></tr><tr><td>0100</td><td>LHLL</td><td>LLLL</td><td/><td/></tr><tr><td>3100</td><td>HHLL</td><td>HLLL</td><td/><td/></tr><tr><td>0103</td><td>LLLH</td><td>LHLH</td><td/><td/></tr><tr><td>3103</td><td>HLLH</td><td>HHLH</td><td/><td/></tr><tr><td>2010</td><td>LLHL</td><td>HHHL</td><td>LHHL</td><td>HLHL</td></tr><tr><td>2013</td><td>LHHH</td><td>HLHH</td><td>LLHH</td><td>HHHH</td></tr><tr><td>7. Ore~</td><td/><td/><td/><td/></tr></table>", |
| "html": null, |
| "num": null |
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| "TABREF5": { |
| "text": "1. Tokenize the orthography so that digraphs such as th. gh. wh, ae.ai, ei, etc., are single units.", |
| "type_str": "table", |
| "content": "<table><tr><td>2. Parse the string of tokens into syllables (assigning =onsonants to</td></tr><tr><td>the right when the location of the syllable boundary is</td></tr><tr><td>ambiguous).</td></tr><tr><td>3. Strip off the final consonant.</td></tr><tr><td>4. For each syllable</td></tr><tr><td>are marked H.</td></tr></table>", |
| "html": null, |
| "num": null |
| }, |
| "TABREF7": { |
| "text": "Level 2 suffixes are called stress neutral because they do not move stress.", |
| "type_str": "table", |
| "content": "<table><tr><td>al</td></tr><tr><td>are found at level l, Greek and Germanic al~tes such as hereto#,</td></tr><tr><td>un#. under#. #hess. #/y are found at level 2, and compounding is</td></tr><tr><td>found at level 3. The term level refers to Mohanan's theory of Level</td></tr><tr><td>Ordered Morphology and Phonology [Mohanan] which builds upon a</td></tr><tr><td>number of well-known differences between + boundary affixes (level I)</td></tr><tr><td>and # boundary affixes (level 2).</td></tr><tr><td>\u2022 Distributional Evidence: It is common to find a level [ affix inside</td></tr><tr><td>the scope of a level 2 affix (e.g., nn#in +terned and form +al#ly),</td></tr><tr><td>but not the other way around (e.g., *in+un#terned and</td></tr><tr><td>\u2022 form#1y +al).</td></tr></table>", |
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| "TABREF9": { |
| "text": ". primary stress can back up onto the prefix: (e.g., telegraphy). Secondly, certain level 1 suffixes such as +ity seem to induce a remarkable stress shift (e.g., sfiper#conductor and si~per#conductDity), in violation of level ordering as far as I can see.", |
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| "content": "<table><tr><td>[For level 1 suffutes, the program assumes the prefixes are marked light</td><td/><td/></tr><tr><td>and that they are extrametricai in verbs, but not in nouns. Prefix</td><td/><td/></tr><tr><td>extrametrieality accounts for the well-known alternation p~rmit (noun)</td><td/><td/></tr><tr><td>versus permlt (verb). Both have L-weight (recall the prefix is L)o</td><td/><td/></tr><tr><td>but the noun has initial struts since the final syllable is extrametrical</td><td/><td/></tr><tr><td>~hereas the verb has final stress since the initial syllable is</td><td/><td/></tr><tr><td>extrametrical. Extrametricality is required here, __hec:_use otherwise</td><td/><td/></tr><tr><td>both the noun and verb would receive initial stress.</td><td/><td/></tr><tr><td>tt. Ety=aetn</td><td/><td/></tr><tr><td>The stress rules outlined above work very well for the bulk of the</td><td/><td/></tr><tr><td>language, but they do have difficulties with certain loan words. For</td><td/><td/></tr><tr><td>instance, consider the Italian word tort6nL By the reasoning outlined</td><td/><td/></tr><tr><td>above, tortbni ought to stress like c;,lcuii since both words have the</td><td/><td/></tr><tr><td>same part of speech and the same syllable weights, but obviously, it</td><td/><td/></tr><tr><td>doesn't. In tact. almost all Italian loan words have penultimate stress,</td><td/><td/></tr><tr><td>as illustrated by the Italian surnames: Aldrigh~ttL Angel~tti. Beli&ti.</td><td/><td/></tr><tr><td>/ann~cci. Ita[ihno. Lombardlno. Marci~no. Marcbni. Morillo. Oliv~ttL</td><td/><td/></tr><tr><td>It is clear from examples such as these that the stress of Italian loans</td><td/><td/></tr><tr><td>is not dependent upon the weight of the penultimate syllable, unlike</td><td/><td/></tr><tr><td>the stress of native English words. Japanese loan words are perhaps</td><td/><td/></tr><tr><td>even more striking in this respect. They too have a very strong</td><td/><td/></tr><tr><td>tendency toward penultimate stress when (mis)pronounced by English</td><td/><td/></tr><tr><td>speakers: Asah&a. Enom\u2022o.</td><td/><td/></tr><tr><td colspan=\"3\">Prefixes are more difficult than suffixes.</td><td>Examples such as</td></tr><tr><td colspan=\"2\">super +fluou~ (levell</td><td>1), s;,per#conducwr</td><td>(level 2), and</td></tr><tr><td colspan=\"4\">sr, per##market (level 3) illustrate just how difficult it is to assign the</td></tr><tr><td colspan=\"4\">prefix to the correct level. Even with the correct parse, it not a simple</td></tr><tr><td colspan=\"4\">matter to assign stress. In general, level 2 pretixes are stressed like</td></tr><tr><td colspan=\"4\">compounds, assigning primary stress to the left morpheme (e.g.,</td></tr><tr><td colspan=\"4\">\u00a2,ndercarriage) for nouns and to the right for verbs (e.g., undergb) and</td></tr><tr><td colspan=\"4\">adjectives (e.g., ;,ltracons~rvative), though there seem to be two classes</td></tr><tr><td colspan=\"4\">of excentions. First. in technical terms, under certain conditions</td></tr><tr><td>\u2022 Stria M ~</td><td colspan=\"3\">as izatma, acl~lur, lo~rt are really seqm:aces o( se,,erat at~xes. In order</td></tr><tr><td colspan=\"4\">tO avoid some difficult psrun| ~ sm~a par ward. This limitinuGa requires that [ enter ~u~ I da:ided not to allow more than one level I of Icv\u00a9l I sut~x~</td></tr><tr><td>into the Im</td><td/><td/></tr></table>", |
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