Welcome to the Irvine Phonotactic Online Dictionary

Irvine Phonotactic Online Dictionary (IPhOD) is a publicly available collection of 33,432 words and 815,066 pseudowords with corresponding Kucera-Francis frequencies (1967), CMU Pronouncing Dictionary transcriptions (Weide, 1994), phonological neighborhood density, positional probabilities, and second- and third-order phoneme-sequence probabilities. Below, we describe the motivation for the database, estimate computations, and suggestions for use in computational psycholinguistics.

Introduction to IPhOD

A growing body of computational psycholinguistic evidence indicates that we segment (Saffran et al., 1996), respond (Vitevitch et al., 1999), produce (Vitevitch et al., 2004), and remember (Majerus et al., 2004) speech in ways that are affected by phonological frequency information. However, speech research is restricted by the limited number of pronunciation collections or utilities, and those phonemic frequency distributions often derive their estimates narrowly (for instance, using small word collections), or do not take stress variations into consideration where it may be useful. While some collections, notably CELEX, address some of these concerns, they use British stress and pronunciation, which is suboptimal for speech research using American English trained subjects. The Phonotactic Probability Calculator (Vitevitch & Luce, 2004) uses American English pronunciations to compute position-specific phonotactic probabilities, but provides no density estimates, frequency weighting options, or stress considerations. Despite growing interest in phonotactic information, it remains unavailable or difficult to derive for novel hypotheses.

The current version (1.3) of the Irvine Phonotactic Online Dictionary (IPhOD) is a collection of phonotactic estimates calculated across a broad sample to enable precise verbal stimuli selection for speech research and application in cognitive science, computational linguistics, and natural language processing. IPhOD contains phonotactic and density estimates, American English transcriptions of 2-17 phonemes, and word frequencies for 33,432 words and 815,066 pseudowords. Pseudowords are defined here as word-like transcriptions consisting entirely of phoneme-pairs from real English words. Pseudowords like these are used in computational psycholinguistics to study non-semantic language processes, since they have little meaning or association but are consistent enough with a language to sound like typical words. The collection and searches using variable and range specification are freely available online in the Tools section at http://lcbr.ss.uci.edu/ or http://www.iphod.com.

Each IPhOD entry contains an American English phonetic transcription from the Carnegie-Mellon Pronouncing Dictionary (Weide, 1994), and Kucera-Francis written word frequencies (1967) from the MRC Psycholinguistic Dictionary (Wilson, 1988). Neighborhood density and word averaged phoneme-sequence probabilities were extrapolated from those data using the same formulas for words and pseudowords, so that entries of either type could be chosen using identical criteria. IPhOD is calculated broadly, over the entire word set in calculations for phonotactic probability and neighborhood density, similar to Vitevitch and Luce (1999).

Estimates contained in IPhOD, by column:

References

Griffin, Zenzi M. and Bock, Kathryn. 1998. Constraint, Word Frequency, and the Relationship between Lexical Processing Levels in Spoken Word Production. Journal of Memory and Language, 38(3): 313-338.

Hulme, C.; Roodenrys, S.; Schweickert, R.; Brown, G.D.A.; Martin, S.; and Stuart, G. 1997. Wordfrequency effects on short-term memory tasks. Journal of Experimental Psychology - Learning, Memory and Cognition, 23(5): 1217–1232.

Kucera, Henry and Francis, W. Nelson. 1967. Computational analysis of present-day American English. Providence, Brown University Press.

Majerus, Steve; Van der Linden, Martial; Mulder, Ludivine; Meulemans, Thierry; and Peters, Frederic 2004. Verbal short-term memory reflects the sublexical organization of the phonological language network. Journal of Memory and Language, 51(2):297-306.

Saffran, Jenny R.; Newport, Elissa L.; and Aslin, Richard N. 1996. Word Segmentation: The Role of Distributional Cues. Journal of Memory and Language, 35(4):606–621.

Vitevitch, Michael S.; Armbr¨uster, Jonna; and Chu, Shinying. 2004. Sublexical and Lexical Representations in Speech Production: Effects of Phonotactic Probability and Onset Density. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2):514-529.

Vitevitch, Michael S.; Luce, Paul A.; Pisoni, David B.; and Auer, Edward T. 1999. Phonotactics, Neighborhood Activation, and Lexical Access for Spoken Words. Brain and Language, 68(1):306-311.

Vitevitch, Michael S. and Luce, Paul A. 2004. A Web-based interface to calculate phonotactic probability for words and nonwords in English. Behavior Research Methods, Instruments, & Computers 36 (3): 481–487.

Weide, Robert L. 1994. CMU Pronouncing Dictionary. http://www.speech.cs.cmu.edu/cgi-bin/cmudict.

Wilson, M. 1988. The MRC Psycholinguistic Database: Machine Readable Dictionary, Version 2. Behavioural ResearchMethods, Instruments and Computers, 20(1), 6-11.