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REGULAR ARTICLES

Ham or hamster? Eye-tracking evidence of a clear speech benefit for word segmentation in quiet and in noise

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Pages 609-631 | Received 23 Apr 2023, Accepted 24 Mar 2024, Published online: 04 May 2024

References

  • Allopenna, P. D., Magnuson, J. S., & Tanenhaus, M. K. (1998). Tracking the time course of spoken word recognition using eye movements: Evidence for continuous mapping models. Journal of Memory and Language, 38(4), 419–439. https://doi.org/10.1006/jmla.1997.2558
  • Barr, D. J. (2008). Analyzing “visual world” eyetracking data using multilevel logistic regression. Journal of Memory and Language, 59(4), 457–474. https://doi.org/10.1016/j.jml.2007.09.002
  • Ben-David, B. M., Chambers, C. G., Daneman, M., Pichora-Fuller, M. K., Reingold, E. M., & Schneider, B. A. (2011). Effects of aging and noise on real-time spoken word recognition: Evidence from eye movements. Journal of Speech, Language, and Hearing Research, 54(1), 243–262. https://doi.org/10.1044/1092-4388(2010/09-0233)
  • Boersma, P., & Weenink, D. (2021). Praat: Doing phonetics by computer [Computer program]. http://www.praat.org/
  • Bradlow, A. R., & Alexander, J. A. (2007). Semantic and phonetic enhancements for speech-in-noise recognition by native and non-native listeners. The Journal of the Acoustical Society of America, 121(4), 2339–2349. https://doi.org/10.1121/1.2642103
  • Bradlow, A. R., & Bent, T. (2002). The clear speech effect for non-native listeners. The Journal of the Acoustical Society of America, 112(1), 272–284. https://doi.org/10.1121/1.1487837
  • Bradlow, A. R., Kraus, N., & Hayes, E. (2003). Speaking clearly for children with learning disabilities: Sentence perception in noise. Journal of Speech, Language, and Hearing Research, 46(1), 80–97. https://doi.org/10.1044/1092-4388(2003/007)
  • Brouwer, S., & Bradlow, A. R. (2016). The temporal dynamics of spoken word recognition in adverse listening conditions. Journal of Psycholinguistic Research, 45(5), 1151–1160. https://doi.org/10.1007/s10936-015-9396-9
  • Brown, M., Salverda, A. P., Dilley, L. C., & Tanenhaus, M. K. (2011). Expectations from preceding prosody influence segmentation in online sentence processing. Psychonomic Bulletin and Review, 18(6), 1189–1196. https://doi.org/10.3758/s13423-011-0167-9
  • Buz, E., Tanenhaus, M. K., & Jaeger, T. F. (2016). Dynamically adapted context-specific hyper-articulation: Feedback from interlocutors affects speakers’ subsequent pronunciations. Journal of Memory and Language, 89, 68–86. https://doi.org/10.1016/j.jml.2015.12.009
  • Cho, T., & Keating, P. (2009). Effects of initial position versus prominence in English. Journal of Phonetics, 37(4), 466–485. https://doi.org/10.1016/j.wocn.2009.08.001
  • Cho, T., & Keating, P. A. (2001). Articulatory and acoustic studies on domain-initial strengthening in Korean. Journal of Phonetics, 29(2), 155–190. https://doi.org/10.1006/jpho.2001.0131
  • Cho, T., McQueen, J. M., & Cox, E. A. (2007). Prosodically driven phonetic detail in speech processing: The case of domain-initial strengthening in English. Journal of Phonetics, 35(2), 210–243. https://doi.org/10.1016/j.wocn.2006.03.003
  • Cohn, M., Pycha, A., & Zellou, G. (2021). Intelligibility of face-masked speech depends on speaking style: Comparing casual, clear, and emotional speech. Cognition, 210, Article 104570. https://doi.org/10.1016/j.cognition.2020.104570
  • Cole, R. A., Jakimik, J., & Cooper, W. E. (1980). Segmenting speech into words. The Journal of the Acoustical Society of America, 67(4), 1323–1332. https://doi.org/10.1121/1.384185
  • Conwell, E., Horvath, G., Kuznia, A., & Agauas, S. J. (2023). Developmental consistency in the use of subphonemic information during real-time sentence processing. Language, Cognition and Neuroscience, 38(6), 860–871. https://doi.org/10.1080/23273798.2022.2159993
  • Cooper, R. M. (1974). The control of eye fixation by the meaning of spoken language. Cognitive Psychology, 6(1), 84–107. https://doi.org/10.1016/0010-0285(74)90005-X
  • Costa, A., Albareda, B., & Santesteban, M. (2008). Assessing the presence of lexical competition across languages: Evidence from the Stroop task. Bilingualism: Language and Cognition, 11(1), 121–131. https://doi.org/10.1017/S1366728907003252
  • Cutler, A. (2012). Native listening: Language experience and the recognition of spoken words. The MIT Press. https://doi.org/10.7551/mitpress/9012.001.0001
  • Cutler, A., & Butterfield, S. (1992). Rhythmic cues to speech segmentation: Evidence from juncture misperception. Journal of Memory and Language, 31(2), 218–236. https://doi.org/10.1016/0749-596X(92)90012-M
  • Cutler, A., & Carter, D. M. (1987). The predominance of strong initial syllables in the English vocabulary. Computer Speech and Language, 2(3–4), 133–142. https://doi.org/10.1016/0885-2308(87)90004-0
  • Cutler, A., & Norris, D. (1988). The role of strong syllables in segmentation for lexical access. Journal of Experimental Psychology: Human Perception and Performance, 14(1), 113–121. https://doi.org/10.1037/0096-1523.14.1.113
  • Cychosz, M., Edwards, J. R., Munson, B., & Johnson, K. (2019). Spectral and temporal measures of coarticulation in child speech. The Journal of the Acoustical Society of America, 146(6), EL516–EL522. https://doi.org/10.1121/1.5139201
  • Dahan, D., Magnuson, J. S., & Tanenhaus, M. K. (2001). Time course of frequency effects in spoken-word recognition: Evidence from eye movements. Cognitive Psychology, 42(4), 317–367. https://doi.org/10.1006/cogp.2001.0750
  • Dahan, D., Magnuson, J. S., Tanenhaus, M. K., & Hogan, E. M. (2001). Subcategorical mismatches and the time course of lexical access: Evidence for lexical competition. Language and Cognitive Processes, 16(5–6), 507–534. https://doi.org/10.1080/01690960143000074
  • Davis, M. H., Marslen-Wilson, W. D., & Gaskell, M. G. (2002). Leading up the lexical garden path: Segmentation and ambiguity in spoken word recognition. Journal of Experimental Psychology: Human Perception and Performance, 28(1), 218–244. https://doi.org/10.1037/0096-1523.28.1.218
  • de Jong, K. J. (1995). The supraglottal articulation of prominence in English: Linguistic stress as localized hyperarticulation. The Journal of the Acoustical Society of America, 97(1), 491–504. https://doi.org/10.1121/1.412275
  • de Jong, K. J. (2004). Stress, lexical focus, and segmental focus in English: Patterns of variation in vowel duration. Journal of Phonetics, 32(4), 493–516. https://doi.org/10.1016/j.wocn.2004.05.002
  • Dilley, L. C., & McAuley, J. D. (2008). Distal prosodic context affects word segmentation and lexical processing. Journal of Memory and Language, 59(3), 294–311. https://doi.org/10.1016/j.jml.2008.06.006
  • Duez, D. (1992). Second formant locus-nucleus patterns: An investigation of spontaneouos French speech. Speech Communication, 11(4–5), 417–427. https://doi.org/10.1016/0167-6393(92)90047-B
  • Duñabeitia, J. A., Crepaldi, D., Meyer, A. S., New, B., Pliatsikas, C., Smolka, E., & Brysbaert, M. (2018). Multipic: A standardized set of 750 drawings with norms for six European languages. Quarterly Journal of Experimental Psychology, 71(4), 808–816. https://doi.org/10.1080/17470218.2017.1310261
  • Eisner, F., & McQueen, J. M. (2018). Speech perception. In Sharon Thompson-Schill (Ed.), Stevens’ handbook of experimental psychology and cognitive neuroscience (pp. 1–46). Wiley. https://doi.org/10.1002/9781119170174.epcn301
  • Ferguson, S. H., & Kewley-Port, D. (2002). Vowel intelligibility in clear and conversational speech for normal-hearing and hearing-impaired listeners. The Journal of the Acoustical Society of America, 112(1), 259–271. https://doi.org/10.1121/1.1482078
  • Ferguson, S. H., & Kewley-Port, D. (2007). Talker differences in clear and conversational speech: Acoustic characteristics of vowels. Journal of Speech, Language, and Hearing Research, 50(5), 1241–1255. https://doi.org/10.1044/1092-4388(2007/087)
  • Ferguson, S. H., & Quené, H. (2014). Acoustic correlates of vowel intelligibility in clear and conversational speech for young normal-hearing and elderly hearing-impaired listeners. The Journal of the Acoustical Society of America, 135(6), 3570–3584. https://doi.org/10.1121/1.4874596
  • Fernandes, T., Kolinsky, R., & Ventura, P. (2010). The impact of attention load on the use of statistical information and coarticulation as speech segmentation cues. Attention, Perception, & Psychophysics, 72(6), 1522–1532. https://doi.org/10.3758/APP.72.6.1522
  • Fernandes, T., Ventura, P., & Kolinsky, R. (2007). Statistical information and coarticulation as cues to word boundaries: A matter of signal quality. Perception and Psychophysics, 69(6), 856–864. https://doi.org/10.3758/BF03193922
  • Fischer, B. (1992). Saccadic reaction time: Implications for reading, dyslexia, and visual cognition (K. Rayner, Ed.; pp. 31–45). Springer. https://doi.org/10.1007/978-1-4612-2852-3_3
  • Fougeron, C., & Keating, P. A. (1997). Articulatory strengthening at edges of prosodic domains. The Journal of the Acoustical Society of America, 101(6), 3728–3740. https://doi.org/10.1121/1.418332
  • Frauenfelder, U. H., & Peeters, G. (1990). Lexical segmentation in TRACE: An exercise in simulation. In G. T. M. Altmann (Ed.), Cognitive models of speech processing: Psycholinguistic and computational perspectives (pp. 50–86). MIT Press.
  • Frost, R. L. A., Monaghan, P., & Tatsumi, T. (2017). Domain-general mechanisms for speech segmentation: The role of duration information in language learning. Journal of Experimental Psychology: Human Perception and Performance, 43(3), 466–476. https://doi.org/10.1037/xhp0000325
  • Gerosa, M., Lee, S., Giuliani, D., & Narayanan, S. (2006). Analyzing children’s speech: An acoustic study of consonants and consonant-vowel transition. In 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings (pp. 393–396). IEEE.
  • Gilbert, R. C., Chandrasekaran, B., & Smiljanic, R. (2014). Recognition memory in noise for speech of varying intelligibility. The Journal of the Acoustical Society of America, 135(1), 389–399. https://doi.org/10.1121/1.4838975
  • Gow, D. W., & Gordon, P. C. (1995). Lexical and prelexical influences on word segmentation: Evidence from priming. Journal of Experimental Psychology: Human Perception and Performance, 21(2), 344–359. https://doi.org/10.1037/0096-1523.21.2.344
  • Greenberg, S., Carvey, H., Hitchcock, L., & Chang, S. (2003). Temporal properties of spontaneous speech – a syllable-centric perspective. Journal of Phonetics, 31(3–4), 465–485. https://doi.org/10.1016/j.wocn.2003.09.005
  • Guo, Z.-C., & Smiljanić, R. (2021). Speaking clearly improves speech segmentation by statistical learning under optimal listening conditions. Laboratory Phonology: Journal of the Association for Laboratory Phonology, 12(1), 14. https://doi.org/10.5334/labphon.310
  • Guo, Z.-C., & Smiljanic, R. (2023). Speakers coarticulate less in response to both real and imagined communicative challenges: An acoustic analysis of the LUCID corpus. Journal of Phonetics, 97, Article 101210. https://doi.org/10.1016/j.wocn.2022.101210
  • Hannagan, T., Magnuson, J. S., & Grainger, J. (2013). Spoken word recognition without a TRACE. Frontiers in Psychology, 4, 1–17. https://doi.org/10.3389/fpsyg.2013.00563
  • Hastie, T. J., & Tibshirani, R. (1990). Generalized additive models. Chapman & Hall/CRC.
  • Hay, J. S. F., & Diehl, R. L. (2007). Perception of rhythmic grouping: Testing the iambic/trochaic law. Perception and Psychophysics, 69(1), 113–122. https://doi.org/10.3758/BF03194458
  • Hazan, V., & Baker, R. (2011). Acoustic-phonetic characteristics of speech produced with communicative intent to counter adverse listening conditions. The Journal of the Acoustical Society of America, 130(4), 2139–2152. https://doi.org/10.1121/1.3623753
  • Hintz, F., & Scharenborg, O. (2016, September 8–12). The effect of background noise on the activation of phonological and semantic information during spoken-word recognition. In Proceedings of INTERSPEECH (pp. 2816–2820). https://doi.org/10.21437/Interspeech.2016-882
  • Huettig, F., Rommers, J., & Meyer, A. S. (2011). Using the visual world paradigm to study language processing: A review and critical evaluation. Acta Psychologica, 137(2), 151–171. https://doi.org/10.1016/j.actpsy.2010.11.003
  • Karuza, E. A., Newport, E. L., Aslin, R. N., Starling, S. J., Tivarus, M. E., & Bavelier, D. (2013). The neural correlates of statistical learning in a word segmentation task: An fMRI study. Brain and Language, 127(1), 46–54. https://doi.org/10.1016/j.bandl.2012.11.007
  • Keating, P., Cho, T., Fougeron, C., & Hsu, C.-S. (2004). Domain-initial articulatory strengthening in four languages. In J. Local, R. Ogden, & R. Temple (Eds.), Phonetic interpretation papers in laboratory phonology VI (pp. 145–163). Cambridge University Press. https://doi.org/10.1017/CBO9780511486425.009
  • Keerstock, S., & Smiljanić, R. (2018). Effects of intelligibility on within- and cross-modal sentence recognition memory for native and non-native listeners. The Journal of the Acoustical Society of America, 144(5), 2871–2881. https://doi.org/10.1121/1.5078589
  • Keerstock, S., & Smiljanić, R. (2019). Clear speech improves listeners’ recall. The Journal of the Acoustical Society of America, 146(6), 4604–4610. https://doi.org/10.1121/1.5141372
  • Krause, J. C., & Braida, L. D. (2004). Acoustic properties of naturally produced clear speech at normal speaking rates. The Journal of the Acoustical Society of America, 115(1), 362–378. https://doi.org/10.1121/1.1635842
  • Krull, D. (1989). Second formant locus patterns as a measure of consonant-vowel coarticulation. Phonetic Experimental Research at the Institute of Linguistics University of Stockholm (PERILUS), 10, 87–108.
  • Lam, J., Tjaden, K., & Wilding, G. (2012). Acoustics of clear speech: Effect of instruction. Journal of Speech, Language, and Hearing Research, 55(6), 1807–1821. https://doi.org/10.1044/1092-4388(2012/11-0154)
  • Lin, X., & Zhang, D. (1999). Inference in generalized additive mixed models by using smoothing splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 61(2), 381–400. https://doi.org/10.1111/1467-9868.00183
  • Lindblom, B. (1990). Explaining phonetic variation: A sketch of the H&H theory. In W. J. Hardcastle & A. Marchal (Eds.), Speech production and speech modelling (pp. 403–439). Springer. https://doi.org/10.1007/978-94-009-2037-8_16
  • Liu, S., Del Rio, E., Bradlow, A. R., & Zeng, F.-G. (2004). Clear speech perception in acoustic and electric hearing. The Journal of the Acoustical Society of America, 116(4), 2374–2383. https://doi.org/10.1121/1.1787528
  • Luce, P. A. (1986). A computational analysis of uniqueness points in auditory word recognition. Perception & Psychophysics, 39(3), 155–158. https://doi.org/10.3758/BF03212485
  • Magnuson, J. S., Dixon, J. A., Tanenhaus, M. K., & Aslin, R. N. (2007). The dynamics of lexical competition during spoken word recognition. Cognitive Science, 31(1), 133–156. https://doi.org/10.1080/03640210709336987
  • Marian, V., Bartolotti, J., Chabal, S., & Shook, A. (2012). CLEARPOND: Cross-linguistic easy-access resource for phonological and orthographic neighborhood densities. PLoS One, 7(8), e43230. https://doi.org/10.1371/journal.pone.0043230
  • Marian, V., & Spivey, M. (2003). Competing activation in bilingual language processing: Within- and between-language competition. Bilingualism: Language and Cognition, 6(2), 97–115. https://doi.org/10.1017/s1366728903001068
  • Marslen-Wilson, W. D. (1987). Functional parallelism in spoken word-recognition. Cognition, 25(1–2), 71–102. https://doi.org/10.1016/0010-0277(87)90005-9
  • Mattys, S. L., & Bortfeld, H. (2017). Speech segmentation. In M. G. Gaskell & J. Mirković (Eds.), Speech perception and spoken word recognition (pp. 55–75). Routledge.
  • Mattys, S. L., Davis, M. H., Bradlow, A. R., & Scott, S. K. (2012). Speech recognition in adverse conditions: A review. Language and Cognitive Processes, 27(7–8), 953–978. https://doi.org/10.1080/01690965.2012.705006
  • Mattys, S. L., White, L., & Melhorn, J. F. (2005). Integration of multiple speech segmentation cues: A hierarchical framework. Journal of Experimental Psychology: General, 134(4), 477–500. https://doi.org/10.1037/0096-3445.134.4.477
  • McAuliffe, M., Socolof, M., Mihuc, S., Wagner, M., & Sonderegger, M. (2017). Montreal forced aligner: Trainable text-speech alignment using Kaldi. In Proceedings of Interspeech 2017 (pp. 498–502). https://doi.org/10.21437/Interspeech.2017-1386
  • McClelland, J. L., & Elman, J. L. (1986). The TRACE model of speech perception. Cognitive Psychology, 18(1), 1–86. https://doi.org/10.1016/0010-0285(86)90015-0
  • McMurray, B., Farris-Trimble, A., & Rigler, H. (2017). Waiting for lexical access: Cochlear implants or severely degraded input lead listeners to process speech less incrementally. Cognition, 169, 147–164. https://doi.org/10.1016/j.cognition.2017.08.013
  • McQueen, J. M. (1996). Word spotting. Language and Cognitive Processes, 11(6), 695–699. https://doi.org/10.1080/016909696387114
  • McQueen, J. M., Cutler, A., Briscoe, T., & Norris, D. (1995). Models of continuous speech recognition and the contents of the vocabulary. Language and Cognitive Processes, 10(3–4), 309–331. https://doi.org/10.1080/01690969508407098
  • Meemann, K., & Smiljanić, R. (2022). Intelligibility of noise-adapted and clear speech in energetic and informational maskers for native and nonnative listeners. Journal of Speech, Language, and Hearing Research, 65(4), 1263–1281. https://doi.org/10.1044/2021_JSLHR-21-00175
  • Mirman, D. (2014). Growth curve analysis and visualization using R. Taylor & Francis.
  • Mirman, D., Dixon, J. A., & Magnuson, J. S. (2008). Statistical and computational models of the visual world paradigm: Growth curves and individual differences. Journal of Memory and Language, 59(4), 475–494. https://doi.org/10.1016/j.jml.2007.11.006
  • Moon, S. J., & Lindblom, B. (1994). Interaction between duration, context, and speaking style in English stressed vowels. The Journal of the Acoustical Society of America, 96(1), 40–55. https://doi.org/10.1121/1.410492
  • Nenadić, F., & Tucker, B. V. (2020). Computational modelling of an auditory lexical decision experiment using jTRACE and TISK. Language, Cognition and Neuroscience, 35(10), 1326–1354. https://doi.org/10.1080/23273798.2020.1764600
  • Newport, E. L., & Aslin, R. N. (2004). Learning at a distance I. Statistical learning of non-adjacent dependencies. Cognitive Psychology, 48(2), 127–162. https://doi.org/10.1016/S0010-0285(03)00128-2
  • Norris, D. (1994). Shortlist: A connectionist model of continuous speech recognition. Cognition, 52(3), 189–234. https://doi.org/10.1016/0010-0277(94)90043-4
  • Ordin, M., Polyanskaya, L., Laka, I., & Nespor, M. (2017). Cross-linguistic differences in the use of durational cues for the segmentation of a novel language. Memory and Cognition, 45(5), 863–876. https://doi.org/10.3758/s13421-017-0700-9
  • Ou, S.-C., & Guo, Z.-C. (2021). The differential effects of vowel and onset consonant lengthening on speech segmentation: Evidence from Taiwanese Southern Min. The Journal of the Acoustical Society of America, 149(3), 1866–1877. https://doi.org/10.1121/10.0003751
  • Payton, K. L., Uchanski, R. M., & Braida, L. D. (1994). Intelligibility of conversational and clear speech in noise and reverberation for listeners with normal and impaired hearing. The Journal of the Acoustical Society of America, 95(3), 1581–1592. https://doi.org/10.1121/1.408545
  • Peelle, J. E., & van Engen, K. J. (2021). Time stand still: Effects of temporal window selection on eye tracking analysis. Collabra: Psychology, 7(1), 1–9. https://doi.org/10.1525/collabra.25961
  • Pelucchi, B., Hay, J. F., & Saffran, J. R. (2009). Statistical learning in a natural language by 8-month-old infants. Child Development, 80(3), 674–685. https://doi.org/10.1111/j.1467-8624.2009.01290.x
  • Picheny, M. A., Durlach, N. I., & Braida, L. D. (1986). Speaking clearly for the hard of hearing. II: Acoustic characteristics of clear and conversational speech. Journal of Speech and Hearing Research, 29(4), 434–446. https://doi.org/10.1044/jshr.2904.434
  • Pichora-Fuller, M. K., Goy, H., & Van Lieshout, P. (2010). Effect on speech intelligibility of changes in speech production influenced by instructions and communication environments. Seminars in Hearing, 31(2), 77–94. https://doi.org/10.1055/s-0030-1252100
  • Porretta, V., Kyröläinen, A. J., van Rij, J., & Järvikivi, J. (2018). Visual world paradigm data: From preprocessing to nonlinear time-course analysis. Smart Innovation, Systems and Technologies, 73, 268–277. https://doi.org/10.1007/978-3-319-59424-8_25
  • Quené, H. (1993). Segment durations and accent as cues to word segmentation in Dutch. Journal of the Acoustical Society of America, 94(4), 2027–2035. https://doi.org/10.1121/1.407504
  • R Core Team. (2020). R: A language and environment for statistical computing (4.0.1). R Foundation for Statistical Computing. https://www.r-project.org/
  • Rönnberg, J., Rudner, M., Lunner, T., & Zekveld, A. (2010). When cognition kicks in: Working memory and speech understanding in noise. Noise and Health, 12(49), 263. https://doi.org/10.4103/1463-1741.70505
  • Rossion, B., & Pourtois, G. (2004). Revisiting Snodgrass and Vanderwart’s object pictorial set: The role of surface detail in basic-level object recognition. Perception, 33(2), 217–236. https://doi.org/10.1068/p5117
  • Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274(5294), 1926–1928. https://doi.org/10.1126/science.274.5294.1926
  • Saffran, J. R., Newport, E. L., & Aslin, R. N. (1996). Word segmentation: The role of distributional cues. Journal of Memory and Language, 35(4), 606–621. https://doi.org/10.1006/jmla.1996.0032
  • Salverda, A. P., Dahan, D., & McQueen, J. M. (2003). The role of prosodic boundaries in the resolution of lexical embedding in speech comprehension. Cognition, 90(1), 51–89. https://doi.org/10.1016/S0010-0277(03)00139-2
  • Shatzman, K. B., & McQueen, J. M. (2006). Prosodic knowledge affects the recognition of newly acquired words. Psychological Science, 17(5), 372–377. https://doi.org/10.1111/j.1467-9280.2006.01714.x
  • Shuai, L., & Malins, J. G. (2017). Encoding lexical tones in jTRACE: A simulation of monosyllabic spoken word recognition in Mandarin Chinese. Behavior Research Methods, 49(1), 230–241. https://doi.org/10.3758/s13428-015-0690-0
  • Shukla, M., Nespor, M., & Mehler, J. (2007). An interaction between prosody and statistics in the segmentation of fluent speech. Cognitive Psychology, 54(1), 1–32. https://doi.org/10.1016/j.cogpsych.2006.04.002
  • Smiljanić, R. (2021). Clear speech perception. In L. C. Nygaard, J. Pardo, D. Pisoni, & R. Remez (Eds.), The handbook of speech perception (2nd ed., pp. 177–205). Wiley. https://doi.org/10.1002/9781119184096.ch7
  • Smiljanić, R., & Bradlow, A. R. (2005). Production and perception of clear speech in Croatian and English. The Journal of the Acoustical Society of America, 118(3), 1677–1688. https://doi.org/10.1121/1.2000788
  • Smiljanić, R., & Bradlow, A. R. (2008a). Stability of temporal contrasts across speaking styles in English and Croatian. Journal of Phonetics, 36(1), 91–113. https://doi.org/10.1016/j.wocn.2007.02.002
  • Smiljanić, R., & Bradlow, A. R. (2008b). Temporal organization of English clear and conversational speech. The Journal of the Acoustical Society of America, 124(5), 3171–3182. https://doi.org/10.1121/1.2990712
  • Smiljanić, R., & Bradlow, A. R. (2009). Speaking and hearing clearly: Talker and listener factors in speaking style changes. Language and Linguistics Compass, 3(1), 236–264. https://doi.org/10.1111/j.1749-818X.2008.00112.x
  • Smiljanić, R., & Gilbert, R. C. (2017). Acoustics of clear and noise-adapted speech in children, young, and older adults. Journal of Speech, Language, and Hearing Research, 60(11), 3081–3096. https://doi.org/10.1044/2017_JSLHR-S-16-0130
  • Spivey, M. J., & Marian, V. (1999). Cross talk between native and second languages: Partial activation of an irrelevant lexicon. Psychological Science, 10(3), 281–284. https://doi.org/10.1111/1467-9280.00151
  • Strauss, T. J., Harris, H. D., & Magnuson, J. S. (2007). jTRACE: A reimplementation and extension of the TRACE model of speech perception and spoken word recognition. Behavior Research Methods, 39(1), 19–30. https://doi.org/10.3758/BF03192840
  • Tanenhaus, M. K., Spivey-Knowlton, M. J., Eberhard, K. M., & Sedivy, J. C. (1995). Integration of visual and linguistic information in spoken language comprehension. Science, 268(5217), 1632–1634. https://doi.org/10.1126/science.7777863
  • ten Bosch, L., Boves, L., & Ernestus, M. (2022). DIANA, a process-oriented model of human auditory word recognition. Brain Sciences, 12(5), 681. https://doi.org/10.3390/brainsci12050681
  • ten Bosch, L., Boves, L., Tucker, B., & Ernestus, M. (2015). DIANA: Towards computational modeling reaction times in lexical decision in North American English. In Proceedings of Interspeech 2015 (pp. 1576–1580). https://doi.org/10.21437/Interspeech.2015-366
  • Thiessen, E. D., & Saffran, J. R. (2007). Learning to learn: Infants’ acquisition of stress-based strategies for word segmentation. Language Learning and Development, 3(1), 73–100. https://doi.org/10.1207/s15473341lld0301_3
  • Toro, J. M., Sinnett, S., & Soto-Faraco, S. (2005). Speech segmentation by statistical learning depends on attention. Cognition, 97(2), B25–B34. https://doi.org/10.1016/j.cognition.2005.01.006
  • Tremblay, A., Broersma, M., & Coughlin, C. E. (2018). The functional weight of a prosodic cue in the native language predicts the learning of speech segmentation in a second language. Bilingualism, 21(3), 640–652. https://doi.org/10.1017/S136672891700030X
  • Tremblay, A., Broersma, M., Coughlin, C. E., & Choi, J. (2016). Effects of the native language on the learning of fundamental frequency in second-language speech segmentation. Frontiers in Psychology, 7, 1–15. https://doi.org/10.3389/fpsyg.2016.00985
  • Tremblay, A., Kim, S., Shin, S., & Cho, T. (2021). Re-examining the effect of phonological similarity between the native- and second-language intonational systems in second-language speech segmentation. Bilingualism: Language and Cognition, 24(2), 401–413. https://doi.org/10.1017/S136672892000053X
  • Tremblay, A., Spinelli, E., Coughlin, C. E., & Namjoshi, J. (2018). Syntactic cues take precedence over distributional cues in native and non-native speech segmentation. Language and Speech, 61(4), 615–631. https://doi.org/10.1177/0023830918801392
  • Tyler, M. D., & Cutler, A. (2009). Cross-language differences in cue use for speech segmentation. The Journal of the Acoustical Society of America, 126(1), 367–376. https://doi.org/10.1121/1.3129127
  • Uchanski, R. M. (2005). Clear speech. In D. Pisoni & R. Remez (Eds.), The handbook of speech perception (pp. 207–235). Blackwell.
  • Uchanski, R. M., Choi, S. S., Braida, L. D., Reed, C. M., & Durlach, N. I. (1996). Speaking clearly for the hard of hearing IV: Further studies of the role of speaking rate. Journal of Speech, Language, and Hearing Research, 39(3), 494–509. https://doi.org/10.1044/jshr.3903.494
  • van der Feest, S. V. H., Blanco, C. P., & Smiljanic, R. (2019). Influence of speaking style adaptations and semantic context on the time course of word recognition in quiet and in noise. Journal of Phonetics, 73, 158–177. https://doi.org/10.1016/j.wocn.2019.01.003
  • Van Engen, K. J., Chandrasekaran, B., & Smiljanić, R. (2012). Effects of speech clarity on recognition memory for spoken sentences. PLoS One, 7(9), e43753. https://doi.org/10.1371/journal.pone.0043753
  • van Engen, K. J., Dey, A., Runge, N., Spehar, B., Sommers, M. S., & Peelle, J. E. (2020). Effects of age, word frequency, and noise on the time course of spoken word recognition. Collabra: Psychology, 6(1), Article 17247. https://doi.org/10.1525/collabra.17247
  • van Rij, J., Hendriks, P., van Rijn, H., Baayen, R. H., & Wood, S. N. (2019). Analyzing the time course of pupillometric data. Trends in Hearing, 23, 1–22. https://doi.org/10.1177/2331216519832483
  • White, L. (2018). Segmentation of speech. In S.-A. Rueschemeyer & M. G. Gaskell (Eds.), The Oxford handbook of psycholinguistics (pp. 4–30). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198786825.013.1
  • White, L., Benavides-Varela, S., & Mády, K. (2020). Are initial-consonant lengthening and final-vowel lengthening both universal word segmentation cues? Journal of Phonetics, 81, Article 100982. https://doi.org/10.1016/j.wocn.2020.100982
  • White, L., Mattys, S. L., Stefansdottir, L., & Jones, V. (2015). Beating the bounds: Localized timing cues to word segmentation. The Journal of the Acoustical Society of America, 138(2), 1214–1220. https://doi.org/10.1121/1.4927409
  • White, L., Mattys, S. L., & Wiget, L. (2012). Segmentation cues in conversational speech: Robust semantics and fragile phonotactics. Frontiers in Psychology, 3, 1–9. https://doi.org/10.3389/fpsyg.2012.00375
  • Wieling, M. (2018). Analyzing dynamic phonetic data using generalized additive mixed modeling: A tutorial focusing on articulatory differences between L1 and L2 speakers of English. Journal of Phonetics, 70, 86–116. https://doi.org/10.1016/j.wocn.2018.03.002
  • Winter, B., & Wieling, M. (2016). How to analyze linguistic change using mixed models, growth curve analysis and generalized additive modeling. Journal of Language Evolution, 1(1), 7–18. https://doi.org/10.1093/jole/lzv003
  • Wood, S. N. (2006). Generalized additive models: An introduction with R. Chapman and Hall/CRC. https://doi.org/10.1201/9781420010404
  • Wood, S. N. (2021). mgcv: Mixed GAM computation vehicle with automatic smoothness estimation (1.8.36). cran.r-project.org/web/packages/mgcv
  • Zekveld, A. A., Kramer, S. E., & Festen, J. M. (2011). Cognitive load during speech perception in noise: The influence of age, hearing loss, and cognition on the pupil response. Ear and Hearing, 32(4), 498–510. https://doi.org/10.1097/AUD.0b013e31820512bb

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