From phoneme to morpheme
Abstract
The following investigation presents a constructional procedure segmenting an utterance in a way which correlates well with word and morpheme boundaries. The procedure requires a large set of utterances, elicited in a certain manner from an informant (or found in a very large corpus); and it requires that all the utterances be written in the same phonemic representation, determined without reference to morphemes. It then investigates a particular distributional relation among the phonemes in the utterances thus collected; and on the basis of this relation among the phonemes, it indicates particular points of segmentation within one utterance at a time. For example, in the utterance /hiyzkwikər/ He's quicker it will indicate segmentation at the points marked by dots: /hiy.z.kwik.ər/; and it will do so purely by comparing this phonemic sequence with the phonemic sequences of other utterances.
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The transitional probability between two sounds, when tracked across a corpus of utterances, will generally be greatest when the two sounds are within the same word.
“Returning to the domain of word segmentation, the transitional probability between two sounds, when tracked across a corpus of utterances, will generally be greatest when the two sounds are within the same word.”
From Statistical learning of tone sequences by human infants and adults (1999) · cites this paper as Harris (1955)
When computed across word boundaries, probabilities of sound pairs should generally be lower.
“When computed across word boundaries, probabilities of sound pairs should generally be lower, reflecting the decreased constraints at boundaries noted by Harris (1955).”
From Statistical learning of tone sequences by human infants and adults (1999) · cites this paper as Harris (1955)
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Statistical learning by 8-month-old infants
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996) · Science · doi:10.1126/science.274.5294.1926 · Cited by 5,659 · see citing works
The faculty of language: what is it, who has it, and how did it evolve?
Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002) · Science · doi:10.1126/science.298.5598.1569 · Cited by 5,189 · see citing works
Three Factors in Language Design
Chomsky, N. A. D. T. (2005) · Linguistic Inquiry · doi:10.1162/0024389052993655 · Cited by 2,668 · see citing works
Ellis, N. C. (2002) · Studies in Second Language Acquisition · doi:10.1017/s0272263102002024 · Cited by 2,230 · see citing works
Statistical learning of tone sequences by human infants and adults
Saffran, J. R., Johnson, E. K., Aslin, R. N., & Newport, E. L. (1999) · Cognition · doi:10.1016/s0010-0277(98)00075-4 · Cited by 1,429 · see citing works
“When computed across word boundaries, probabilities of sound pairs should generally be lower, reflecting the decreased constraints at boundaries noted by Harris (1955).”
BackgroundInfluentialWord Segmentation: The Role of Distributional Cues
Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996) · Journal of Memory and Language · doi:10.1006/jmla.1996.0032 · Cited by 1,405 · see citing works
“More-least to Harris (1955), who proposed that linguists working on unfamiliar languages might over, the structure of their test was such that even these results might be in part the outcomediscover the individual word units by counting how many phones can succeed a given string. of test strategies…”
BackgroundLearning at a distance I. Statistical learning of non-adjacent dependencies.
Newport, E., & Aslin, R. (2004) · Cognitive Psychology · doi:10.1016/s0010-0285(03)00128-2 · Cited by 735 · see citing works
“Indeed, most words in natural languages are comprised of consistent sound patterns among adjacent syllables, and the transitional probability relations we examined in our miniature language studies were similar to those exhibited in real human languages ( Harris, 1955 ).”
ResultUnsupervised Learning of the Morphology of a Natural Language
Goldsmith, J. (2001) · Computational Linguistics · doi:10.1162/089120101750300490 · Cited by 790 · see citing works
“This was first proposed by Zellig Harris (1955, 1967), and further developed by others, notably by Hafer and Weiss (1974).”
BackgroundMethodThe faculty of language: what is it, who has it, and how did it evolve?
HAUSER, M. D., Chomsky, N., & Fitch, W. T. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511817755.002 · Cited by 580 · see citing works
Distributional Information: A Powerful Cue for Acquiring Syntactic Categories
Redington, M., Chater, N., & Finch, S. (1998) · Cognitive Science · doi:10.1207/s15516709cog2204_2 · Cited by 535 · see citing works
“These procedures were useful heuristic guides rather than algorithms (though see Harris, 1955).”
MethodDistributional regularity and phonotactic constraints are useful for segmentation
Brent, M. R., & Cartwright, T. A. (1996) · Cognition · doi:10.1016/s0010-0277(96)00719-6 · Cited by 514 · see citing works
“Word-based Strategies Olivier (1968) proposed a procedure that maintains a lexicon and uses it for segmenting.”
MethodA Bayesian framework for word segmentation: exploring the effects of context.
Goldwater, S., Griffiths, T., & Johnson, M. A. (2009) · Cognition · doi:10.1016/j.cognition.2009.03.008 · Cited by 506 · see citing works
“Most previous work on statistical word segmentation is based on the observation that transitions from one syllable or phoneme to the next tend to be less predictable at word boundaries than within words (Harris, 1955; Saffran et al., 1996a).”
Bortfeld, H., Morgan, J. L., Golinkoff, R. M., & Rathbun, K. (2005) · Psychological Science · doi:10.1111/j.0956-7976.2005.01531.x · Cited by 427 · see citing works
“Such a sequence of probabilities can indicate that /mamiz/ forms a word—Mommy’s—and the sounds that follow belong to other words (Harris, 1955; Hayes & Clark, 1970; Saffran et al., TABLE 2”
Phonotactic cues for segmentation of fluent speech by infants.
Mattys, S., & Jusczyk, P. (2001) · Cognition · doi:10.1016/s0010-0277(00)00109-8 · Cited by 386 · see citing works
“Brent & Cartwright, 1996; Goodsitt, Morgan, & Kuhl, 1993; Harris, 1955; Hayes & Clark, 1970; Saffran, Aslin, & Newport, 1996.”
Unsupervised models for morpheme segmentation and morphology learning
Creutz, M., & Lagus, K. (2007) · ACM Transactions on Speech and Language Processing · doi:10.1145/1187415.1187418 · Cited by 340 · see citing works
“Jacquemin [1997] discovers morphological variants of multiword collocations, for example, ‘longitudinal recording’ vs.”
BackgroundThe Developmental Trajectory of Nonadjacent Dependency Learning
Gómez, R. L., & Maye, J. (2005) · Infancy · doi:10.1207/s15327078in0702_4 · Cited by 314 · see citing works
“Indeed, much of this work is reminiscent of themes found in early associationist approaches to language acquisition (e.g., Harris, 1955 ).”
BackgroundFriedemann Pulvermüller, A. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511615528 · Cited by 645 · see citing works
Statistical clustering and the contents of the infant vocabulary
Swingley, D. (2005) · Cognitive Psychology · doi:10.1016/j.cogpsych.2004.06.001 · Cited by 306 · see citing works
“The idea that words may be identified via distributional analysis is not new (e.g. Brent & Cartwright, 1996; Harris, 1955; Hayes & Clark, 1970; Pinker, 1984) but infants discovery of words has received less attention than infants discovery of phonetic categories.”
Influential3 Parts and wholes: Implicative patterns in inflectional paradigms
Ackerman, F., Blevins, J. P., & Malouf, R. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0003 · Cited by 305 · see citing works
Erickson, L., & Thiessen, E. D. (2015) · Developmental Review · doi:10.1016/j.dr.2015.05.002 · Cited by 246 · see citing works
Speech Perception and Language Acquisition in the First Year of Life
Gervain, J., & Mehler, J. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.100408 · Cited by 263 · see citing works
“Proponents of structural linguistics (Harris 1955) and information theory (Shannon 1948) have long recognized that the statistical information encoded in language provides cues to its constituent units (e.g., morphemes and words) and structural patterns.”
BackgroundLeading Up the Lexical Garden Path: Segmentation and Ambiguity in Spoken Word Recognition
Davis, M. H., Marslen-Wilson, W., & Gaskell, M. (2002) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/0096-1523.28.1.218 · Cited by 256 · see citing works
“Another distributional account assumes that chunking the speech stream into frequently occurring phoneme sequences will produce segmentation into linguistically coherent units (Brent & Cartwright, 1996; Perruchet & Vinter, 1998; Wolff, 1977; see Harris, 1955, for a related approach in linguistics).”
BackgroundThe growth of language: Universal Grammar, experience, and principles of computation
Yang, C. D., Crain, S., Berwick, R. C., Chomsky, N., & Bolhuis, J. J. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.12.023 · Cited by 241 · see citing works
Temporal predictive codes for spoken words in auditory cortex
Gagnepain, P., Henson, R. N., & Davis, M. H. (2012) · Current Biology · doi:10.1016/j.cub.2012.02.015 · Cited by 235 · see citing works
A brain perspective on language mechanisms: from discrete neuronal ensembles to serial order
Friedemann Pulvermüller, A. (2002) · Progress in Neurobiology · doi:10.1016/s0301-0082(02)00014-x · Cited by 206 · see citing works
“Whereas within a word, a phoneme is followed by one out of 5–20 other phonemes (Harris, 1955), the number of possible successors of a word can reach the order of 10 4 .”
BackgroundWord segmentation by letter successor varieties
Hafer, M. A., & Weiss, S. F. (1974) · Information Processing & Management · doi:10.1016/0020-0271(74)90044-8 · Cited by 207 · see citing works
An interaction between prosody and statistics in the segmentation of fluent speech.
Shukla, M., Nespor, M., & Mehler, J. (2007) · Cognitive Psychology · doi:10.1016/j.cogpsych.2006.04.002 · Cited by 196 · see citing works
“How do infants learn to segment fluent speech into a series of words? Statistical strategies were proposed for the segmentation of words, based on distributional properties over sub-lexical units like phonemes or syllables (e.g., Harris, 1955; Brent & Cartwright, 1996; Dahan & Brent, 1999; Batchelder, 2002; Swingley,…”
BackgroundMethodThe multiple codes of nucleotide sequences
Trifonov, E. N. (1989) · Bulletin of Mathematical Biology · doi:10.1007/bf02460081 · Cited by 176 · see citing works
Speech segmentation and word discovery: a computational perspective
Brent, M. R. (1999) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(99)01350-9 · Cited by 163 · see citing works
Rapid learning of syllable classes from a perceptually continuous speech stream.
Endress, A., & Bonatti, L. (2007) · Cognition · doi:10.1016/j.cognition.2006.09.010 · Cited by 151 · see citing works
“…sensitivity to statistical cues in the speech signal, in particular to transition probabilities (TPs), could in principle solve this problem (e.g., Harris, 1955; Hayes & Clark, 1970, but see Yang, 2004).1 Recent research has shown that adults and infants can indeed segment a continuous speech…”
BackgroundThe Infant's Auditory World: Hearing, Speech, and the Beginnings of Language
Saffran, J. R., Werker, J. F., & Werner, L. A. (2007) · Wiley eBooks · doi:10.1002/9780470147658.chpsy0202 · Cited by 155 · see citing works
Representation of lexical form.
McLennan, C. T., Luce, P. A., & Charles-Luce, J. (2003) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.29.4.539 · Cited by 140 · see citing works
“Studdert-Kennedy (1974) provided one of the earliest explicit articulations of this kind of mediated lexical access model, which itself drew inspiration from linguistic theory (see Bloomfield, 1933; Chomsky & Halle, 1968; Harris, 1955; Kenstowicz & Kisseberth, 1979; see also Jusczyk & Luce, 2002, for a discussion).”
BackgroundMilin, P., Kuperman, V., Kostić, A., & Baayen, R. H. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0010 · Cited by 138 · see citing works
Phonological phrase boundaries constrain lexical access II. Infant data
Gout, A., Christophe, A., & Morgan, J. L. (2004) · Journal of Memory and Language · doi:10.1016/j.jml.2004.07.002 · Cited by 128 · see citing works
Speech Perception and Spoken Word Recognition: Past and Present
Jusczyk, P., & Luce, P. A. (2002) · Ear and Hearing · doi:10.1097/00003446-200202000-00002 · Cited by 144 · see citing works
“In the field of linguistics, a major goal was to devise rigorous scientific procedures that would yield a correct structural description of a particular language when provided with a detailed corpus of utterances (Bloomfield, 1933; Harris, 1955).”
BackgroundUnsupervised Learning of Morphology
Hammarström, H., & Borin, L. (2011) · Computational Linguistics · doi:10.1162/coli_a_00050 · Cited by 128 · see citing works
“Usually and justifiedly, the work of Harris (1955, 1967) is given as the starting point of ULM.”
InfluentialMorph-based speech recognition and modeling of out-of-vocabulary words across languages
Creutz, M., Hirsimäki, T., Kurimo, M., Puurula, A., Pylkkönen, J., Siivola, V., Varjokallio, M., Arisoy, E., Saraçlar, M., & Stolcke, A. (2007) · ACM Transactions on Speech and Language Processing · doi:10.1145/1322391.1322394 · Cited by 127 · see citing works
Constructing a Proto-Lexicon: An Integrative View of Infant Language Development
Johnson, E. K. (2015) · Annual Review of Linguistics · doi:10.1146/annurev-linguistics-011415-040616 · Cited by 119 · see citing works
“Harris (1955) described a phoneme-based distributional learning approach that could help field linguists find morphemes in an unfamiliar language.”
Background1 Introduction: Analogy in grammar
(2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0001 · Cited by 118 · see citing works
Connectionist and Statistical Approaches to Language Acquisition: A Distributional Perspective
Redington, M., & Chater, N. (1998) · Language and Cognitive Processes · doi:10.1080/016909698386500 · Cited by 107 · see citing works
“A further cue, suggested by early work in distributional linguistics (e.g. Harris, 1955), and utilised in the models described later, is the redundancy, or predictability of the speech stream.”
BackgroundLexical effects on compensation for coarticulation: the ghost of Christmash past
Magnuson, J. S., McMurray, B., Tanenhaus, M. K., et al. (2003) · Cognitive Science · doi:10.1207/s15516709cog2702_6 · Cited by 102 · see citing works
Unsupervised Lexicon Discovery from Acoustic Input
Lee, C.-Y., O'Donnell, T. J., & Glass, J. R. (2015) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00146 · Cited by 95 · see citing works
“The problem has been the focus of many years of intense research, and there are a large variety of proposals in the literature (Harris, 1955; Saffran et al., 1996a; Harris, 1955; Olivier, 1968; Saffran et al., 1996b; Brent, 1999b; Frank et al., 2010; Frank et al., 2013).”
BackgroundMilin, P., Kuperman, V., Kostić, A., & Baayen, R. H. (2009) · doi:10.1093/acprof:oso/9780199547548.001.0001 · Cited by 101 · see citing works
Parallel processing in speech perception with local and global representations of linguistic context
Brodbeck, C. J., Bhattasali, S., Heredia, A. A. L. C., Resnik, P., Simon, J. Z., & Lau, E. F. (2022) · eLife · doi:10.7554/elife.72056 · Cited by 97 · see citing works
9 Modeling analogy as probabilistic grammar
Albright, A. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0009 · Cited by 95 · see citing works
Friedemann Pulvermüller, A. (2003) · Cambridge University Press eBooks · doi:10.1017/cbo9780511615528.002 · Cited by 94 · see citing works
Dominey, P. F., & Ramus, F. (2000) · Language and Cognitive Processes · doi:10.1080/016909600386129 · Cited by 94 · see citing works
“Rhythm class: According to Pike (1945) and Abercrombie (1967).”
BackgroundTopicalization, inversion, and complementizers in English (1992)
Culicover, P. W. (2013) · doi:10.1093/acprof:oso/9780199660230.003.0008 · Cited by 86 · see citing works
Co-occurrence statistics as a language-dependent cue for speech segmentation.
Saksida, A., Langus, A., & Nespor, M. (2017) · Developmental Science · doi:10.1111/desc.12390 · Cited by 45 · see citing works
“Across languages, syllable pairs with higher statistical coherence tend to belong to the same word (Harris, 1955; Hayes & Clark, 1970).”
Statistical language learning: computational, maturational, and linguistic constraints
Newport, E. (2016) · Language and Cognition · doi:10.1017/langcog.2016.20 · Cited by 41 · see citing works
“…linguists had long provided suggestions for what these cues might be: the words of the language are those sound sequences that regularly recur within a corpus, in contrast to word boundaries, which vary depending on what words happen to follow one another in a particular sentence (Harris, 1955 ).”
BackgroundDo 11-month-old French Infants Process Articles?
Hallé, P., Durand, C., & de Boysson-Bardies, B. (2008) · Language and Speech · doi:10.1177/00238309080510010301 · Cited by 78 · see citing works
“…retain word-forms on the basis of how cohesive they are in terms of co-occurring sounds (cf. Saffran, Newport, & Aslin, 1996; Swingley, 2005a; the idea dates back to Harris, 1955), speech chunks such as gâteau and le gâteau might indeed be both retained as possible word-forms in a “protolexicon.””
Unsupervised morphological parsing of Bengali
Dasgupta, S., & Ng, V. (2007) · Computers and the Humanities · doi:10.1007/s10579-007-9031-y · Cited by 58 · see citing works
“For instance, Harris (1955) develops a strategy for identifying morpheme boundaries that checks whether the number of different letters following a sequence of letters exceeds some given threshold.”
BackgroundMethodIntegrating unsupervised and supervised word segmentation: The role of goodness measures
Zhao, H. Y., & Kit, C. (2010) · Information Sciences · doi:10.1016/j.ins.2010.09.008 · Cited by 58 · see citing works
“In principle, Harris’s idea underlies both AV and BE; that is, the branching uncertainty is higher at a boundary in between language units such as morphemes or words than at other places.”
MethodEvolutionary Linguistics: A New Look at an Old Landscape
HAUSER, M. D., Barner, D., & O’Donnell, T. (2007) · Language Learning and Development · doi:10.1080/15475440701225394 · Cited by 58 · see citing works
“One early proposal on how they might do this, originally due to Harris (1955) , was that they might be sensitive to the transition statistics of syllables or phonemes in natural language.”
BackgroundAn unsupervised Hindi stemmer with heuristic improvements
Pandey, A. K., & Siddiqui, T. J. (2008) · doi:10.1145/1390749.1390765 · Cited by 53 · see citing works
How Infant Speech Perception Contributes to Language Acquisition
Gervain, J., & Werker, J. F. (2008) · Language and Linguistics Compass · doi:10.1111/j.1749-818x.2008.00089.x · Cited by 51 · see citing works
“Fourthly, it has long been recognized that the statistical regularities of phoneme co-occurrences are also reliable indicators of morpheme and word boundaries (Harris 1955; Brent and Cartwright 1996).”
BackgroundMorphology and Language Acquisition
Lignos, C., & Yang, C. D. (2016) · Cambridge University Press eBooks · doi:10.1017/9781139814720.027 · Cited by 51 · see citing works
“One approach is using sequences of characters to identify morpheme boundaries— an idea first presented by Harris (1955)—either by an algorithmic approach (Hafer and Weiss 1974; Keshava and Pitler 2006) or developing n-gram-based statistical models (e.g., Spiegler et al. 2009).”
MethodLanguage Acquisition and the Discovery of Phrase Structure
Wolff, J. G. (1980) · Language and Speech · doi:10.1177/002383098002300303 · Cited by 46 · see citing works
“Also relevant are studies by linguists in which the main motive is the development of tools for linguistic analysis (Gammon, 1969; Harris, 1955) and there is a sizeable literature on discovery procedures intended to have practical utility in artificial intelligence, robotics and pattern recognition…”
BackgroundKhorsi, A. (2012) · Natural Language Engineering · doi:10.1017/s1351324912000071 · Cited by 45 · see citing works
“The oldest published work on unsupervised word segmentation is due to Zelig Harris who suggested in the 1950 s a process to break a phonetic text into morphemes (Harris 1955) using only successors numbering.”
BackgroundTOWARDS SPEECH TRANSLATION OF NON WRITTEN LANGUAGES
Besacier, L., Zhou, B., & Gao, Y. (2006) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt.2006.326795 · Cited by 42 · see citing works
“Our algorithm gathers different approaches already applied to the word segmentation problem: a) use predictability of phonemes: the basic idea here, first suggested by [9], is that the number of distinct phonemes that are possible successors of the preceding string reduces rapidly with the length of that string unless…”
MethodA reconsideration of Dative Movements (1972)
Jackendoff, R. S., & Culicover, P. W. (2013) · doi:10.1093/acprof:oso/9780199660230.003.0011 · Cited by 42 · see citing works
Thiessen, E. D., & Erickson, L. C. (2013) · Current Directions in Psychological Science · doi:10.1177/0963721413476035 · Cited by 42 · see citing works
“This has been investigated especially with respect to segmenting words embedded in fluent speech, because sounds within a word are more predictable than sounds across word boundaries (e.g., Harris, 1955).”
BackgroundSequences and Codes: Fundamentals of Biomolecular Cryptology
Konopka, A. K. (1994) · Elsevier eBooks · doi:10.1016/b978-0-08-092596-7.50008-3 · Cited by 42 · see citing works
2 Principal parts and degrees of paradigmatic transparency
Finkel, R. A., & Stump, G. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0002 · Cited by 40 · see citing works
Kazakov, D., & Manandhar, S. (2001) · Machine Learning · doi:10.1023/a:1007629103294 · Cited by 39 · see citing works
“Other algorithms for unsupervised learning of word segmentation using corpus statistics are also known (Harris, 1955).”
MethodLexical, syntactic, and stress-pattern cues for speech segmentation.
Sanders, L. D., & Neville, H. (2000) · Journal of Speech, Language and Hearing Research · doi:10.1044/jslhr.4306.1301 · Cited by 46 · see citing works
“Harris (1955) suggested that the probability of hearing any two syllables in succession is higher if the syllables both occur within a word (for example, “baby”) than if the syllables occur as the last sound in one word and the first sound in the next (for example “-by doll”).”
BackgroundWordSeg: Standardizing unsupervised word form segmentation from text
Bernard, M., Thiollière, R., Saksida, A., Loukatou, G. R., Larsen, E., Johnson, M., Fibla, L., Emmanuel Dupoux, A., Daland, R., Cao, X., et al. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01223-3 · Cited by 35 · see citing works
“…have enjoyed a fair amount of attention for the last several decades (e.g., Brent & Cartwright, 1996; Gambell & Yang, 2005; Goldwater et al., 2009; Harris, 1955), as they reveal that the latter may be close enough to infants’ segmentation to make predictions that can be validated via direct…”
BackgroundParaMor: Finding Paradigms across Morphology
Monson, C., Carbonell, J., Lavie, A., et al. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85760-0_115 · Cited by 35 · see citing works
“To filter out left-leaning clusters, ParaMor adapts a strategy due to Harris (1955), who detects morpheme boundaries by examining word internal character variation.”
MethodList, J., Pathmanathan, J. S., Lopez, P., & Bapteste, E. P. (2016) · Biology Direct · doi:10.1186/s13062-016-0145-2 · Cited by 33 · see citing works
“Especially automatic approaches to the unsupervised detection of morphemes date back to the 1950s [116], and many different methods have been proposed over the last decade [117–119].”
MethodSimple Morpheme Labelling in Unsupervised Morpheme Analysis
Bernhard, D. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85760-0_112 · Cited by 34 · see citing works
“This idea is recurrent in research on the segmentation of words into morphemes (see for instance [4,5,6]).”
BackgroundThe statistical signature of morphosyntax: A study of Hungarian and Italian infant-directed speech
Gervain, J., & Erra, R. G. (2012) · Cognition · doi:10.1016/j.cognition.2012.06.010 · Cited by 33 · see citing works
A Comparative Study of Minimally Supervised Morphological Segmentation
Ruokolainen, T., Kohonen, O., Sirts, K., et al. (2016) · Computational Linguistics · doi:10.1162/coli_a_00243 · Cited by 30 · see citing works
“For example, merely for the CRF model alone, there exist several proposed semi-supervised learning approaches (Jiao et al. 2006; Mann and McCallum 2008; Wang et al. 2009).”
BackgroundStatistically coherent labels facilitate categorization in 8-month-olds
Erickson, L. C., Thiessen, E. D., & Graf Estes, K. (2014) · Journal of Memory and Language · doi:10.1016/j.jml.2014.01.002 · Cited by 27 · see citing works
“One possibility is that infants rely on a cross-linguistically consistent characteristic of words, namely, that syllables that comprise words cluster together with greater reliability than syllables that occur incidentally across word boundaries (Harris, 1955; Hayes & Clark, 1970).”
BackgroundBilingualism and statistical learning: Lessons from studies using artificial languages
Weiss, D. J., Schwob, N., & Lebkuecher, A. L. (2019) · Bilingualism Language and Cognition · doi:10.1017/s1366728919000579 · Cited by 27 · see citing works
Automatic Speech-to-Text Transcription in Arabic
Lamel, L. F., Messaoudi, A., & Gauvain, J. (2009) · ACM Transactions on Asian Language Information Processing · doi:10.1145/1644879.1644885 · Cited by 25 · see citing works
“2006]), and unsupervised methods (for example, [Harris 1955; Goldsmith 2001; Adda-Decker 2003; Creutz and Lagus 2005]).”
MethodAn Efficient Algorithm for Unsupervised Word Segmentation with Branching Entropy and MDL
Zhikov, V., Takamura, H., & Okumura, M. (2010) · Conference on Empirical Methods in Natural Language Processing · doi:10.1527/tjsai.28.347 · Cited by 34 · see citing works
Implicit language learning: Adults’ ability to segment words in Norwegian
Kittleson, M. M., Aguilar, J. M., Tokerud, G. L., Plante, E., & Asbjørnsen, A. (2010) · Bilingualism · doi:10.1017/s1366728910000039 · Cited by 24 · see citing works
“-PA Author M anuscript N IH -PA Author M anuscript clusters of co-occurring sounds (Harris, 1955).”
BackgroundUnsupervised and Knowledge-Free Morpheme Segmentation and Analysis
Bordag, S. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85760-0_113 · Cited by 24 · see citing works
“based algorithm [ 13 , 12, 10] described and implemented previously [4, 5]. The additional component of morpheme analysis is based on a prototypical implementation described in [7].”
MethodGoldsmith, J. (2005) · Language · doi:10.1353/lan.2005.0127 · Cited by 24 · see citing works
The word as a unit of internal predictability
Mansfield, J. (2021) · Linguistics · doi:10.1515/ling-2020-0118 · Cited by 24 · see citing works
Entropy as an Indicator of Context Boundaries: An Experiment Using a Web Search Engine
Tanaka‐Ishii, K. (2005) · Lecture notes in computer science · doi:10.1007/11562214_9 · Cited by 22 · see citing works
Automatic Word Decompounding for ASR in a Morphologically Rich Language: Application to Amharic
Pellegrini, T., & Lamel, L. F. (2009) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2009.2022295 · Cited by 23 · see citing works
“Finally, some conclusions and perspectives are given.”
Term conflation methods in information retrieval
Gálvez, C., Anegón, F. D. M., & Herrero-Solana, V. (2005) · Journal of Documentation · doi:10.1108/00220410510607507 · Cited by 22 · see citing works
“Another well-known conflation technique is the successor stemmer, based on the work of Harris (1955), segmenting utterances that are spelt phonetically, and creating trees whose labels correspond to a single character (Knuth, 1973).”
MethodLetter constraints within words in printed English
Carson, D. H. (1961) · Kybernetik · doi:10.1007/bf00293854 · Cited by 22 · see citing works
Culicover, P. W. (2013) · doi:10.1093/acprof:oso/9780199660230.001.0001 · Cited by 20 · see citing works
Muncer, S., Knight, D., & Adams, J. W. (2013) · Journal of Psycholinguistic Research · doi:10.1007/s10936-013-9252-8 · Cited by 21 · see citing works
“This is interesting as it accords with some very early attempts to devise methods of segmenting speech into morphemes (Harris 1955).”
Background6 The role of analogy for compound words
Krott, A. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0006 · Cited by 20 · see citing works
Information Theory as a Bridge Between Language Function and Language Form
Futrell, R., & Hahn, M. (2022) · Frontiers in Communication · doi:10.3389/fcomm.2022.657725 · Cited by 20 · see citing works
“This connection between morpheme segmentation, transitional probabilities, and mutual information goes back at least to Harris (1955).”
BackgroundOperationalising salience: definite article reduction in the North of England1
Rácz, P. (2012) · English Language and Linguistics · doi:10.1017/s1360674311000281 · Cited by 13 · see citing works
“Harris (1955) was the first to suggest that linguists can use distributional cues of segments to find word boundaries.”
BackgroundParaMor and Morpho Challenge 2008
Monson, C., Carbonell, J., Lavie, A., et al. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04447-2_128 · Cited by 18 · see citing works
“The character transition approach is exemplified by [8], which builds forward and backward character tries”
BackgroundMethodDistribution-driven morpheme discovery: a computational/experimental study
Baroni, M. (2003) · Yearbook of morphology · doi:10.1007/978-1-4020-1513-7_9 · Cited by 23 · see citing works
“After the pioneering work of Harris in the fifties (see, e.g., Harris 1955) and until very recently, modeling morpheme discovery has been a relatively unpopular research domain.”
MethodNucleotide sequences versus Markov models
Pevzner, P. A. (1992) · Computers & Chemistry · doi:10.1016/0097-8485(92)80036-y · Cited by 18 · see citing works
Inflectional learning as local optimization
Trommer, J., & Bank, S. (2017) · Morphology · doi:10.1007/s11525-017-9304-0 · Cited by 9 · see citing works
“Second, the results of the learning algorithms developed here should be systematically evaluated against the predictions made by segmentation algorithms based purely on the distribution of word forms and segments (Harris 1955, 1967; Langer 1991; Gold-smith 2001).”
BackgroundInfant Perception and Cognition
Colombo, J. A., Brez, C. C., & Curtindale, L. M. (2012) · Wiley eBooks · doi:10.1002/9781118133880.hop206003 · Cited by 17 · see citing works
Unsupervised Morphological Analysis by Formal Analogy
Lavallée, J.-F., & Langlais, P. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15754-7_74 · Cited by 16 · see citing works
“Indeed, Harris [1] described such a system in the fifties.”
Background7 Morphological analogy: Only a beginning
Goldsmith, J. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199547548.003.0007 · Cited by 16 · see citing works
Gervain, J. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64150-2.00016-2 · Cited by 16 · see citing works
Character recognition in context
Thomas, R. B., & Kassler, M. (1967) · Information and Control · doi:10.1016/s0019-9958(67)90042-3 · Cited by 15 · see citing works
Non-canonical Inflection: Data, Formalisation and Complexity Measures
Sagot, B., & Walther, G. (2011) · Communications in computer and information science · doi:10.1007/978-3-642-23138-4_3 · Cited by 14 · see citing works
“This has be done through edit distance measures [8], maximum affix recognition [37,31,71], word insertion tests [39,28,10], and analogies [43,35,49]; – Another method relies on entropy models based on Harris’ hypothesis [34].”
MethodThe role of metacognition in recognition of the content of statistical learning
Ordin, M., & Polyanskaya, L. (2020) · Psychonomic Bulletin & Review · doi:10.3758/s13423-020-01800-0 · Cited by 14 · see citing works
“Conditional statistics measure the predictive relationships between consecutive events (Harris, 1955; Saffran, Aslin, & Newport, 1996).”
Background
- Authors
- Harris, Z. S.
- Corresponding author
- Harris, Zellig S.
- Venue
- Language
- Publisher
- Cambridge University Press (CUP)
- Published
- 1955-06
- Volume
- 31
- Issue
- 2
- Pages
- 190-222
- ISSN
- 0097-8507 (ISSN-L)
- 1535-0665
- OpenAlex
- W4251556668
- Cited by
- 256
- References
- 0
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 2 · 2022: 5 · 2021: 10 · 2020: 13 · 2019: 6 · 2018: 3 · 2017: 10 · 2016: 16 · 2015: 5 · 2014: 9 · 2013: 24 · 2012: 8
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Language (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Keywords
- utterance segmentation, morpheme boundaries, word boundaries, phonemic representation, phoneme sequences
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