Publications

Displaying 101 - 113 of 113
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2013). Towards an end-to-end computational model of speech comprehension: simulating a lexical decision task. In Proceedings of INTERSPEECH 2013: 14th Annual Conference of the International Speech Communication Association (pp. 2822-2826).

    Abstract

    This paper describes a computational model of speech comprehension that takes the acoustic signal as input and predicts reaction times as observed in an auditory lexical decision task. By doing so, we explore a new generation of end-to-end computational models that are able to simulate the behaviour of human subjects participating in a psycholinguistic experiment. So far, nearly all computational models of speech comprehension do not start from the speech signal itself, but from abstract representations of the speech signal, while the few existing models that do start from the acoustic signal cannot directly model reaction times as obtained in comprehension experiments. The main functional components in our model are the perception stage, which is compatible with the psycholinguistic model Shortlist B and is implemented with techniques from automatic speech recognition, and the decision stage, which is based on the linear ballistic accumulation decision model. We successfully tested our model against data from 20 participants performing a largescale auditory lexical decision experiment. Analyses show that the model is a good predictor for the average judgment and reaction time for each word.
  • Timmer, K., Ganushchak, L. Y., Mitlina, Y., & Schiller, N. O. (2013). Choosing first or second language phonology in 125 ms [Abstract]. Journal of Cognitive Neuroscience, 25 Suppl., 164.

    Abstract

    We are often in a bilingual situation (e.g., overhearing a conversation in the train). We investigated whether first (L1) and second language (L2) phonologies are automatically activated. A masked priming paradigm was used, with Russian words as targets and either Russian or English words as primes. Event-related potentials (ERPs) were recorded while Russian (L1) – English (L2) bilinguals read aloud L1 target words (e.g. РЕЙС /reis/ ‘fl ight’) primed with either L1 (e.g. РАНА /rana/ ‘wound’) or L2 words (e.g. PACK). Target words were read faster when they were preceded by phonologically related L1 primes but not by orthographically related L2 primes. ERPs showed orthographic priming in the 125-200 ms time window. Thus, both L1 and L2 phonologies are simultaneously activated during L1 reading. The results provide support for non-selective models of bilingual reading, which assume automatic activation of the non-target language phonology even when it is not required by the task.
  • Tsoukala, C., Frank, S. L., & Broersma, M. (2017). “He's pregnant": Simulating the confusing case of gender pronoun errors in L2 English. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (pp. 3392-3397). Austin, TX, USA: Cognitive Science Society.

    Abstract

    Even advanced Spanish speakers of second language English tend to confuse the pronouns ‘he’ and ‘she’, often without even noticing their mistake (Lahoz, 1991). A study by AntónMéndez (2010) has indicated that a possible reason for this error is the fact that Spanish is a pro-drop language. In order to test this hypothesis, we used an extension of Dual-path (Chang, 2002), a computational cognitive model of sentence production, to simulate two models of bilingual speech production of second language English. One model had Spanish (ES) as a native language, whereas the other learned a Spanish-like language that used the pronoun at all times (non-pro-drop Spanish, NPD_ES). When tested on L2 English sentences, the bilingual pro-drop Spanish model produced significantly more gender pronoun errors, confirming that pronoun dropping could indeed be responsible for the gender confusion in natural language use as well.
  • Ünal, E., & Papafragou, A. (2013). Linguistic and conceptual representations of inference as a knowledge source. In S. Baiz, N. Goldman, & R. Hawkes (Eds.), Proceedings of the 37th Annual Boston University Conference on Language Development (BUCLD 37) (pp. 433-443). Boston: Cascadilla Press.
  • Van Dooren, A., Dieuleveut, A., Cournane, A., & Hacquard, V. (2017). Learning what must and can must and can mean. In A. Cremers, T. Van Gessel, & F. Roelofsen (Eds.), Proceedings of the 21st Amsterdam Colloquium (pp. 225-234). Amsterdam: ILLC.

    Abstract

    This corpus study investigates how children figure out that functional modals
    like must can express various flavors of modality. We examine how modality is
    expressed in speech to and by children, and find that the way speakers use
    modals may obscure their polysemy. Yet, children eventually figure it out. Our
    results suggest that some do before age 3. We show that while root and
    epistemic flavors are not equally well-represented in the input, there are robust
    correlations between flavor and aspect, which learners could exploit to discover
    modal polysemy.
  • Van Dooren, A. (2017). Dutch must more structure. In A. Lamont, & K. Tetzloff (Eds.), NELS 47: Proceedings of the Forty-Seventh Annual Meeting of the North East Linguistic Society (pp. 165-175). Amherst: GLSA.
  • Van Geenhoven, V. (1999). A before-&-after picture of when-, before-, and after-clauses. In T. Matthews, & D. Strolovitch (Eds.), Proceedings of the 9th Semantics and Linguistic Theory Conference (pp. 283-315). Ithaca, NY, USA: Cornell University.
  • Van Putten, S. (2013). The meaning of the Avatime additive particle tsye. In M. Balbach, L. Benz, S. Genzel, M. Grubic, A. Renans, S. Schalowski, M. Stegenwallner, & A. Zeldes (Eds.), Information structure: Empirical perspectives on theory (pp. 55-74). Potsdam: Universitätsverlag Potsdam. Retrieved from http://nbn-resolving.de/urn/resolver.pl?urn=urn:nbn:de:kobv:517-opus-64804.
  • Wagner, A., & Braun, A. (2003). Is voice quality language-dependent? Acoustic analyses based on speakers of three different languages. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 651-654). Adelaide: Causal Productions.
  • Walsh Dickey, L. (1999). Syllable count and Tzeltal segmental allomorphy. In J. Rennison, & K. Kühnhammer (Eds.), Phonologica 1996. Proceedings of the 8th International Phonology Meeting (pp. 323-334). Holland Academic Graphics.

    Abstract

    Tzeltal, a Mayan language spoken in southern Mexico, exhibits allo-morphy of an unusual type. The vowel quality of the perfective suffix is determined by the number of syllables in the stem to which it is attaching. This paper presents previously unpublished data of this allomorphy and demonstrates that a syllable-count analysis of the phenomenon is the proper one. This finding is put in a more general context of segment-prosody interaction in allomorphy.
  • Weber, A., & Smits, R. (2003). Consonant and vowel confusion patterns by American English listeners. In M. J. Solé, D. Recasens, & J. Romero (Eds.), Proceedings of the 15th International Congress of Phonetic Sciences.

    Abstract

    This study investigated the perception of American English phonemes by native listeners. Listeners identified either the consonant or the vowel in all possible English CV and VC syllables. The syllables were embedded in multispeaker babble at three signal-to-noise ratios (0 dB, 8 dB, and 16 dB). Effects of syllable position, signal-to-noise ratio, and articulatory features on vowel and consonant identification are discussed. The results constitute the largest source of data that is currently available on phoneme confusion patterns of American English phonemes by native listeners.
  • Weber, A., & Smits, R. (2003). Consonant and vowel confusion patterns by American English listeners. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 1437-1440). Adelaide: Causal Productions.

    Abstract

    This study investigated the perception of American English phonemes by native listeners. Listeners identified either the consonant or the vowel in all possible English CV and VC syllables. The syllables were embedded in multispeaker babble at three signalto-noise ratios (0 dB, 8 dB, and 16 dB). Effects of syllable position, signal-to-noise ratio, and articulatory features on vowel and consonant identification are discussed. The results constitute the largest source of data that is currently available on phoneme confusion patterns of American English phonemes by native listeners.
  • Zhang, Y., & Yu, C. (2017). How misleading cues influence referential uncertainty in statistical cross-situational learning. In M. LaMendola, & J. Scott (Eds.), Proceedings of the 41st Annual Boston University Conference on Language Development (BUCLD 41) (pp. 820-833). Boston, MA: Cascadilla Press.

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