Johanna Mesch

Johanna Mesch


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Arbetar vid Institutionen för lingvistik
Besöksadress Universitetsvägen 10 C, plan 2-3
Rum C 351
Postadress Institutionen för lingvistik 106 91 Stockholm

Om mig

Docent, ämnesföreträdare för Avdelningen för teckenspråk vid Institutionen för lingvistik, Stockholms universitet

Presentation på teckenspråk
Presentation på svenskt teckenspråk


VT 2018:
  • LIT130/LIT132 Teckenspråk I, Analys av teckenspråkstexter I, 7,5 hp
  • LITFL2 Fortbildningskurs i teckenspråk för lärare, 30 hp (kursansvarig)
  • Handledning av uppsatser
HT 2018:
  • LITU10/LITN12/LITN02, Teckenspråk i teori och praktik I, Dövas kultur och historia, 5 hp
  • TTA435 Teckenspråkstolkning, Taktilt teckenspråk, 5 hp
  • LITU10/LITN12/LITS02, Svenskt teckenspråk II, praktiskt fokus
Här är ett exempel på min föreläsning om teckenspråkets historia.


Min expertis inom taktil teckenspråkskommunikation har varit efterfrågad i flera år, efter min doktorsavhandling Teckenspråk i taktil form – turtagning och frågor i dövblindas samtal på teckenspråk (1998). Jag har haft ett övergripande ansvar för ett treårigt projekt Korpus för det svenska teckenspråket under åren 2009-2011, finansierat av Riksbankens Jubileumsfond. Nu är jag involverad i ett treårigt TATE-projekt Från tal till tecken - att lära sig Svenskt teckenspråk som andraspråk under åren 2017-2019, tillsammans med Krister Schönström. Jag är också involverad i det nationella Swe-Clarin-projektet, tillsammans med Mats Wirén på datorlingvistik.


Aktuella forskningsprojekt:


I urval från Stockholms universitets publikationsdatabas
  • 2018. Johanna Mesch, Krister Schönström. 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community, 121-126

    This paper aims to present part of the project “From Speech to Sign – learning Swedish Sign Language as a second language” which include a learner corpus that is based on data produced by hearing adult L2 signers. The paper describes the design of corpus building and the collection of data for the Corpus in Swedish Sign Language as a Second Language (SSLC-L2). Another component of ongoing work is the creation of a specialized annotation scheme for SSLC-L2, one that differs somewhat from the annotation work in Swedish Sign Language Corpus (SSLC), where the data is based on performance by L1 signers. Also, we will account for and discuss the methodology used to annotate L2 structures.

  • 2018. Nikolaus Riemer Kankkonen (et al.). 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community, 171-174

    In this paper, we describe how we are actively using the Swedish Sign Language (SSL) community in collecting and documenting signs and lexical variation for our language resources, particularly the online Swedish Sign Language Dictionary (SSLD). Apart from using the SSL Corpus as a source of input for new signs and lexical variation in the SSLD, we also involve the community in two ways: first, we interact with SSL signers directly at various venues, collecting signs and judgments about signs; second, we discuss sign usage, lexical variation, and sign formation with SSL signers on social media, particularly through a Facebook group in which we both actively engage in and monitor discussions about SSL. Through these channels, we are able to get direct feedback on our language documentation work and improve on what has become the main lexicographic resource for SSL. We describe the process of simultaneously using corpus data, judgment and elicitation data, and crowdsourcing and discussion groups for enhancing the SSLD, and give examples of findings pertaining to lexical variation resulting from this work.

  • 2018. Lars Wallin, Johanna Mesch.
  • 2018. Carl Börstell (et al.).

    The idea of transitivity as a scalar phenomenon is well known (e.g., Hopper & Thompson 1980; Tsunoda 1985; Haspelmath 2015). However, as with most areas of linguistic study, it has been almost exclusively studied with a focus on spoken languages. A rare exception to this is Kimmelman (2016), who investigates transitivity in Russian Sign Language (RSL) on the basis of corpus data. Kimmelman attempts to establish a transitivity prominence hierarchy of RSL verbs, and compares this ranking to the verb meanings found in the ValPal database (Hartmann, Haspelmath & Bradley 2013). He arrives at the conclusion that using the frequency of overt objects in corpus data is a successful measure of transitivity prominence, and that the prominence ranking of RSL verbs correlate with that found for spoken languages in Haspelmath (2015). In this paper, we expand on these intra- and cross-modal comparisons of transitivity prominence by introducing four other sign languages to the sample: Finnish Sign Language (FinSL), Swedish Sign Language (SSL), Sign Language to the Netherlands (NGT), and German Sign Language (DGS). FinSL and SSL are known to be historically related (cf. Bergman & Engberg-Pedersen 2010), while the other are not related, which allows us to look at both modality and relatedness effects in our sample. Of the 80 core verb meanings in the ValPal database, Kimmelman (2016) included the 25 most frequent verbs in his corpus. For our study, we have annotated all occurrences of these 25 verb meanings in a subset of the corpora of FinSL (2h 40min; 18,446 tokens), SSL (2h 5min; 16,724 tokens), NGT (≈80,000 tokens), and DGS (≈58,000 tokens). We annotate whether a verb occurs with an overt object as well as the type of object (direct, indirect, clausal, or a locative). Looking at the ValPal verb meanings with ≥5 sign tokens in all four new languages, we arrive at 12 verbs that are found in all five sign languages and the spoken languages (SpL) of the ValPal database – see Table 1. In Table 1, we see that there is a general agreement across languages – both signed and spoken – in how transitivity prominent a verb meaning is. Spearman’s rank correlation shows a significant (p<0.05) correlation between all possible pairs except SSL–SpL (p=0.091) and SSL– RSL (p=0.074), corroborating Kimmelman’s finding that there are patterns of transitivity prominence present across languages and modalities. It is interesting that SSL thus diverges from the other sign languages in this sample: this deserves further investigation. We also wanted to investigate the transitivity prominence as a property of individual languages. In order to do so, we took the individual languages of the ValPal database and measured each verb meaning in each language with regard to its transitivity prominence. This meant calculating how many of the verb forms associated with a specific verb meaning took a P argument. Note that this is quite different from calculating transitivity prominence based on corpus data: with corpora, we calculated the proportion of verbal tokens occurring with an overt object, and with the ValPal database, we calculated the proportion of transitive verb associated with a particular concept. We included the 12 verb meanings found across all languages (the five sign languages and 33 spoken languages). We then calculated mean distances across verb meanings and languages, and plotted this with multidimensional scaling in Figure 1. In the figure, we see that the five sign languages form a part of a cluster, suggesting either modality-based similarities, or similarities that come with the difference in data (corpus data rather than lexical data). On the other hand, sign languages as a group are not clearly opposed to spoken languages as a group, which implies that the corpus-based and lexical calculations of transitivity are comparable. Interestingly, FinSL and SSL are not more strongly associated than the other sign languages, which implies that their historical relatedness is not directly relevant to transitivity. In our presentation, we will present the results and the conclusions in more detail, as well as discuss the possibilities of using corpus data to establish valency patterns for languages in the signed modality.

    References Bergman, Brita & Elisabeth Engberg-Pedersen. 2010. Transmission of sign languages in the Nordic countries. In Diane Brentari (ed.), Sign languages: A Cambridge language survey, 74–94. New York, NY: Cambridge University Press.Hartmann, Iren, Martin Haspelmath & Taylor Bradley (eds.). 2013. Valency Patterns Leipzig. Leipzig: Max Planck Institute for Evolutionary Anthropology. Haspelmath, Martin. 2015. Transitivity prominence. In Andrej Malchukov & Bernard Comrie (eds.), Valency classes in the world’s languages: Vol 1 - Introducing the framework, and case studies from Africa and Eurasia, 131–148. Boston, MA: De Gruyter Mouton. Hopper, Paul J. & Sandra A. Thompson. 1980. Transitivity in grammar and discourse. Language 56(2). 251–299. Kimmelman, Vadim. 2016. Transitivity in RSL: A corpus-based account. In Eleni Efthimiou, Stavroula-Evita Fotinea, Thomas Hanke, Julie Hochgesang, Jette Kristoffersen & Johanna Mesch (eds.), Proceedings of the 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining, 117–120. Paris: European Language Resources Association (ELRA). Tsunoda, Tasaku. 1985. Remarks on transitivity. Journal of Linguistics 21(2). 385. doi:10.1017/S0022226700010318.

  • Artikel Signed renga
    2017. Johanna Mesch, Michiko Kaneko. African Studies 76 (3), 381-401

    South African Sign Language (SASL) poetry is still exploring many forms of poetry genres. This article describes the recent development of a new ‘genre’ in sign language poetry: signed renga (group poetry). The article will outline the form – what it is, how it has developed and spread, and why it is an apparently successful poetic genre. A sketch of a workshop from Signing Hands Across the Water 2 (SHAW 2) will also be provided to illustrate how renga emerges out of group work. First we will briefly explain common features of signed renga, drawing on a body of signed renga in British, Irish and Swedish Sign Languages. The second half of the article is an in-depth analysis of one signed renga, titled South Africa, which emerged from the SHAW 2 festival, with a focus on transitions as collaborative performance using shared signing space and eye gaze direction

  • 2016. Johanna Mesch. Language & Communication 50, 22-41

    The current study aims to determine the manual backchannel responses that signers use in Swedish Sign Language discourse by analyzing a subset of the SSL Corpus. The investiga- tion found 20% of the backchannel responses in this data to be manual. The study focuses on the manual backchannel responses that consist of signs (mostly the sign gloss YES) and gesture-like signs (PU “palms up”), and other manual activities, which can occur at a relatively low height in signing space. With respect to age groups, younger signers engage in more weak manual activity than older signers.

Visa alla publikationer av Johanna Mesch vid Stockholms universitet

Senast uppdaterad: 19 juni 2018

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