Publications

Displaying 201 - 216 of 216
  • ten Bosch, L., & Scharenborg, O. (2005). ASR decoding in a computational model of human word recognition. In Interspeech'2005 - Eurospeech, 9th European Conference on Speech Communication and Technology (pp. 1241-1244). ISCA Archive.

    Abstract

    This paper investigates the interaction between acoustic scores and symbolic mismatch penalties in multi-pass speech decoding techniques that are based on the creation of a segment graph followed by a lexical search. The interaction between acoustic and symbolic mismatches determines to a large extent the structure of the search space of these multipass approaches. The background of this study is a recently developed computational model of human word recognition, called SpeM. SpeM is able to simulate human word recognition data and is built as a multi-pass speech decoder. Here, we focus on unravelling the structure of the search space that is used in SpeM and similar decoding strategies. Finally, we elaborate on the close relation between distances in this search space, and distance measures in search spaces that are based on a combination of acoustic and phonetic features.
  • Ten Bosch, L., Boves, L., & Ernestus, M. (2017). The recognition of compounds: A computational account. In Proceedings of Interspeech 2017 (pp. 1158-1162). doi:10.21437/Interspeech.2017-1048.

    Abstract

    This paper investigates the processes in comprehending spoken noun-noun compounds, using data from the BALDEY database. BALDEY contains lexicality judgments and reaction times (RTs) for Dutch stimuli for which also linguistic information is included. Two different approaches are combined. The first is based on regression by Dynamic Survival Analysis, which models decisions and RTs as a consequence of the fact that a cumulative density function exceeds some threshold. The parameters of that function are estimated from the observed RT data. The second approach is based on DIANA, a process-oriented computational model of human word comprehension, which simulates the comprehension process with the acoustic stimulus as input. DIANA gives the identity and the number of the word candidates that are activated at each 10 ms time step.

    Both approaches show how the processes involved in comprehending compounds change during a stimulus. Survival Analysis shows that the impact of word duration varies during the course of a stimulus. The density of word and non-word hypotheses in DIANA shows a corresponding pattern with different regimes. We show how the approaches complement each other, and discuss additional ways in which data and process models can be combined.
  • Trabasso, T., & Ozyurek, A. (1997). Communicating evaluation in narrative understanding. In T. Givon (Ed.), Conversation: Cognitive, communicative and social perspectives (pp. 268-302). Philadelphia, PA: Benjamins.
  • Trilsbeek, P., & Wittenburg, P. (2005). Archiving challenges. In J. Gippert, N. Himmelmann, & U. Mosel (Eds.), Essentials of language documentation (pp. 311-335). Berlin: Mouton de Gruyter.
  • 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.
  • 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 Wijk, C., & Kempen, G. (1982). Kost zinsbouw echt tijd? In R. Stuip, & W. Zwanenberg (Eds.), Handelingen van het zevenendertigste Nederlands Filologencongres (pp. 223-231). Amsterdam: APA-Holland University Press.
  • Van de Weijer, J. (1997). Language input to a prelingual infant. In A. Sorace, C. Heycock, & R. Shillcock (Eds.), Proceedings of the GALA '97 conference on language acquisition (pp. 290-293). Edinburgh University Press.

    Abstract

    Pitch, intonation, and speech rate were analyzed in a collection of everyday speech heard by one Dutch infant between the ages of six and nine months. Components of each of these variables were measured in the speech of three adult speakers (mother, father, baby-sitter) when they addressed the infant, and when they addressed another adult. The results are in line with previously reported findings which are usually based on laboratory or prearranged settings: infant-directed speech in a natural setting exhibits more pitch variation, a larger number of simple intonation contours, and slower speech rate than does adult-directed speech.
  • Van Gijn, R., Hammarström, H., Van de Kerke, S., Krasnoukhova, O., & Muysken, P. (2017). Linguistic Areas, Linguistic Convergence and River Systems in South America. In R. Hickey (Ed.), The Cambridge Handbook of Areal Linguistics (pp. 964-996). Cambridge: Cambridge University Press. doi:10.1017/9781107279872.034.
  • Van Heuven, V. J., Haan, J., Janse, E., & Van der Torre, E. J. (1997). Perceptual identification of sentence type and the time-distribution of prosodic interrogativity markers in Dutch. In Proceedings of the ESCA Tutorial and Research Workshop on Intonation: Theory, Models and Applications, Athens, Greece, 1997 (pp. 317-320).

    Abstract

    Dutch distinguishes at least four sentence types: statements and questions, the latter type being subdivided into wh-questions (beginning with a question word), yes/no-questions (with inversion of subject and finite), and declarative questions (lexico-syntactically identical to statement). Acoustically, each of these (sub)types was found to have clearly distinct global F0-patterns, as well as a characteristic distribution of final rises [1,2]. The present paper explores the separate contribution of parameters of global downtrend and size of accent-lending pitch movements versus aspects of the terminal rise to the human identification of the four sentence (sub)types, at various positions in the time-course of the utterance. The results show that interrogativity in Dutch can be identified at an early point in the utterance. However, wh-questions are not distinct from statements.
  • Zeshan, U. (2005). Sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 558-559). Oxford: Oxford University Press.
  • Zeshan, U. (2005). Question particles in sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 564-567). Oxford: Oxford University Press.
  • Zeshan, U., Pfau, R., & Aboh, E. (2005). When a wh-word is not a wh-word: the case of Indian sign language. In B. Tanmoy (Ed.), Yearbook of South Asian languages and linguistics 2005 (pp. 11-43). Berlin: Mouton de Gruyter.
  • Zeshan, U. (2005). Irregular negatives in sign languages. In M. Haspelmath, M. S. Dryer, D. Gil, & B. Comrie (Eds.), The world atlas of language structures (pp. 560-563). Oxford: Oxford University Press.
  • 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.

Share this page