Melbourne School of Psychological Sciences - Research Publications

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    Beyond Pattern Completion with Short-Term Plasticity
    Shabahang, KD ; Yim, H ; Dennis, SJ (Cognitive Science Society, 2020-01-01)
    In a Linear Associative Net (LAN), all input settles to a single pattern, therefore Anderson, Silverstein, Ritz, and Jones (1977) introduced saturation to force the system to reach other steady-states in the Brain-State-in-a-Box (BSB). Unfortunately, the BSB is limited in its ability to generalize because its responses are restricted to previously stored patterns. We present simulations showing how a Dynamic-Eigen-Net (DEN), a LAN with Short-Term Plasticity (STP), overcomes the single-response limitation. Critically, a DEN also accommodates novel patterns by aligning them with encoded structure. We train a two-slot DEN on a text corpus, and provide an account of lexical decision and judgement-of-grammaticality (JOG) tasks showing how grammatical bi-grams yield stronger responses relative to ungrammatical bi-grams. Finally, we present a simulation showing how a DEN is sensitive to syntactic violations introduced in novel bi-grams. We propose DENs as associative nets with greater promise for generalization than the classic alternatives.
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    Making Sense of Emotion-Sensing: Workshop on Quantifying Human Emotions
    Tag, B ; Webber, S ; Wadley, G ; Bartlett, V ; Goncalves, J ; Koval, P ; Slovak, P ; Smith, W ; Hollenstein, T ; Cox, AL ; Kostakos, V (ASSOC COMPUTING MACHINERY, 2021)
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    SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages
    Pimentel, T ; Ryskina, M ; Mielke, SJ ; Wu, S ; Chodroff, E ; Leonard, B ; Nicolai, G ; Ghanggo Ate, Y ; Khalifa, S ; Habash, N ; El-Khaissi, C ; Goldman, O ; Gasser, M ; Lane, W ; Coler, M ; Oncevay, A ; Montoya Samame, JR ; Silva Villegas, GC ; Ek, A ; Bernardy, J-P ; Shcherbakov, A ; Bayyr-ool, A ; Sheifer, K ; Ganieva, S ; Plugaryov, M ; Klyachko, E ; Salehi, A ; Krizhanovsky, A ; Krizhanovsky, N ; Vania, C ; Ivanova, S ; Salchak, A ; Straughn, C ; Liu, Z ; Washington, JN ; Ataman, D ; Kieraś, W ; Woliński, M ; Suhardijanto, T ; Stoehr, N ; Nuriah, Z ; Ratan, S ; Tyers, FM ; Ponti, EM ; Aiton, G ; Hatcher, RJ ; Prud'hommeaux, E ; Kumar, R ; Hulden, M ; Barta, B ; Lakatos, D ; Szolnok, G ; Ács, J ; Raj, M ; Yarowsky, D ; Cotterell, R ; Ambridge, B ; Vylomova, E (Association for Computational Linguistics, 2021)
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    Windows to wellbeing: Insights from music performance science
    Osborne, M (ISPS, 2021-10-30)
    The emotional life of performers is complex. To perform with freedom, spontaneity, and creativity, they must be prepared to take risks and ‘feel the fear’, but they must also find ways to manage their fear so they can be physically and mentally capable of expressing themselves freely and creatively. A nuanced approach is needed to help performers navigate this territory. Applying interventions to enhance performance requires us to be cognisant to the performer’s stage of development and performance ambitions. These are situated within a myriad of biopsychosocial factors and educational and occupational demands that collectively influence musicians’ health across their lifespan. In this talk I draw from clinical, research and teaching practice to discuss windows to psychological wellbeing - tried and tested approaches to performance anxiety management. My explanation explores basic psychological needs, self-regulated learning principles, performance routines for emotional regulation, and psychological flexibility. Strategies will be suggested for musicians to implement in their performance practice. Reference: Osborne, M.S. (2021, 27-30 October). Windows to wellbeing: Insights from music performance science. Keynote presented at the International Symposium of Performance Science on “Performance Health and Wellbeing”, Montréal, Canada.
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    SIGTYP 2020 Shared Task: Prediction of Typological Features
    Bjerva, J ; Salesky, E ; Mielke, SJ ; Chaudhary, A ; Giuseppe, C ; Ponti, EM ; Vylomova, E ; Cotterell, R ; Augenstein, I (Association for Computational Linguistics, 2020)
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    SIGTYP 2021 Shared Task: Robust Spoken Language Identification
    Salesky, E ; Abdullah, BM ; Mielke, S ; Klyachko, E ; Serikov, O ; Ponti, EM ; Kumar, R ; Cotterell, R ; Vylomova, E (Association for Computational Linguistics, 2021)
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    Anlirika: An LSTM–CNN Flow Twister for Spoken Language Identification
    Scherbakov, A ; Whittle, L ; Kumar, R ; Singh, S ; Coleman, M ; Vylomova, E (Association for Computational Linguistics, 2021)
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    SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
    Vylomova, E ; White, J ; Salesky, E ; Mielke, SJ ; Wu, S ; Ponti, E ; Maudslay, RH ; Zmigrod, R ; Valvoda, J ; Toldova, S ; Tyers, F ; Klyachko, E ; Yegorov, I ; Krizhanovsky, N ; Czarnowska, P ; Nikkarinen, I ; Krizhanovsky, A ; Pimentel, T ; Hennigen, LT ; Kirov, C ; Nicolai, G ; Williams, A ; Anastasopoulos, A ; Cruz, H ; Chodroff, E ; Cotterell, R ; Silfverberg, M ; Hulden, M (ASSOC COMPUTATIONAL LINGUISTICS-ACL, 2020)