@inproceedings{mcdonald:24018:sign-lang:lrec, author = {McDonald, John C. and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Wolfe, Rosalee}, title = {Multilingual Synthesis of Depictions through Structured Descriptions of Sign: An Initial Case Study}, pages = {244--253}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc}, booktitle = {Proceedings of the {LREC-COLING} 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources}, maintitle = {2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)}, publisher = {{ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)}}, address = {Torino, Italy}, day = {25}, month = may, year = {2024}, isbn = {978-2-493814-30-2}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/24018.html}, doi = {10.63317/2wzky9so2vix}, abstract = {Sign language synthesis systems must contend with an enormous variety of possible target languages across the world, and in many locations, such as Europe, the number of sign languages that can be found in a relatively limited geographical area can be surprising. For such a synthesis system to be widely useful, it must not be limited to only one target language. This presents challenges both for the linguistic models and the animation systems that drive these displays. This paper presents a case study for animating discourse in three target languages, French, Greek and German, generated directly from the same base linguistic description. The case study exploits non-lexical constructs in sign, which are more common among sign languages, while providing a first step for synthesizing those aspects that are different. Further, it suggests a possible path forward to exploring whether linguistic structures in one sign language can be exploited in other sign languages, which might be particularly helpful in under-resourced languages.} } @inproceedings{filhol:22009:sign-lang:lrec, author = {Filhol, Michael and McDonald, John C.}, title = {Representation and Synthesis of Geometric Relocations}, pages = {53--58}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc}, booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {25}, month = jun, year = {2022}, isbn = {979-10-95546-86-3}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22009.html}, doi = {10.63317/3itqun936kbs}, abstract = {One of the key features of signed discourse is the geometric placements of gestural units in signing space. Signers use the geometry of signing space to describe the placements and forms of objects and also use it to contrast participants or locales in a story. Depending on the specific functions of the placement in the discourse, features such as geometric precision, gaze redirection and timing will all differ. A signing avatar must capture these differences to sign such discourse naturally. This paper builds on prior work that animated geometric depictions to enable a signing avatar to more naturally use signing space for opposing participants and concepts in discourse. Building from a structured linguistic description of a signed newscast, they system automatically synthesizes animation that correctly utilizes signing space to lay out the opposing locales in the report. The efficacy of the approach is demonstrated through comparisons of the avatar's motion with the source signing.} } @inproceedings{choudhury:70011:sltat:lrec, author = {Choudhury, Shatabdi}, title = {Analysis of Torso Movement for Signing Avatar Using Deep Learning}, pages = {7--12}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and McDonald, John C. and Shterionov, Dimitar and Wolfe, Rosalee}, booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {24}, month = jun, year = {2022}, isbn = {979-10-95546-82-5}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/2022.sltat-1.2.html}, doi = {10.63317/2gc3q39s3of2}, abstract = {Avatars are virtual or on-screen representations of a human used in various roles for sign language display, including translation and educational tools. Though the ability of avatars to portray acceptable sign language with believable human-like motion has improved in recent years, many still lack the naturalness and supporting motions of human signing. Such details are generally not included in the linguistic annotation. Nevertheless, these motions are highly essential to displaying lifelike and communicative animations. This paper presents a deep learning model for use in a signing avatar. The study focuses on coordinating torso movements and other human body parts. The proposed model will automatically compute the torso rotation based on the avatar's wrist positions. The resulting motion can improve the user experience and engagement with the avatar.} } @inproceedings{dimou:70021:sltat:lrec, author = {Dimou, Athanasia-Lida and Papavassiliou, Vassilis and McDonald, John C. and Goulas, Theodoros and Vasilaki, Kyriaki and Vacalopoulou, Anna and Fotinea, Stavroula-Evita and Efthimiou, Eleni and Wolfe, Rosalee}, title = {Signing Avatar Performance Evaluation within {EASIER} Project}, pages = {39--44}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and McDonald, John C. and Shterionov, Dimitar and Wolfe, Rosalee}, booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {24}, month = jun, year = {2022}, isbn = {979-10-95546-82-5}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/2022.sltat-1.6.html}, doi = {10.63317/3xn8c5z3e5px}, abstract = {The direct involvement of deaf users in the development and evaluation of signing avatars is imperative to achieve legibility and raise trust among synthetic signing technology consumers. A paradigm of constructive cooperation between researchers and the deaf community is the EASIER project , where user driven design and technology development have already started producing results. One major goal of the project is the direct involvement of sign language (SL) users at every stage of development of the project's signing avatar. As developers wished to consider every parameter of SL articulation including affect and prosody in developing the EASIER SL representation engine, it was necessary to develop a steady communication channel with a wide public of SL users who may act as evaluators and can provide guidance throughout research steps, both during the project's end-user evaluation cycles and beyond. To this end, we have developed a questionnaire-based methodology, which enables researchers to reach signers of different SL communities on-line and collect their guidance and preferences on all aspects of SL avatar animation that are under study. In this paper, we report on the methodology behind the application of the EASIER evaluation framework for end-user guidance in signing avatar development as it is planned to address signers of four SLs -Greek Sign Language (GSL), French Sign Language (LSF), German Sign Language (DGS) and Swiss German Sign Language (DSGS)- during the first project evaluation cycle. We also briefly report on some interesting findings from the pilot implementation of the questionnaire with content from the Greek Sign Language (GSL).} } @inproceedings{johnson:70015:sltat:lrec, author = {Johnson, Ronan}, title = {Improved Facial Realism through an Enhanced Representation of Anatomical Behavior in Sign Language Avatars}, pages = {53--58}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and McDonald, John C. and Shterionov, Dimitar and Wolfe, Rosalee}, booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {24}, month = jun, year = {2022}, isbn = {979-10-95546-82-5}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/2022.sltat-1.8.html}, doi = {10.63317/5j5bqi9mfywg}, abstract = {Facial movements and expressions are critical features of signed languages, yet are some of the most challenging to reproduce on signing avatars. Due to the relative lack of research efforts in this area, the facial capabilities of such avatars have yet to receive the approval of those in the Deaf community. This paper revisits the representations of the human face in signed avatars, specifically those based on parameterized muscle simulation such as FACS and the MPEG-4 file definition. An improved framework based on rotational pivots and pre-defined movements is capable of reproducing realistic, natural gestures and mouthings on sign language avatars. The new approach is more harmonious with the underlying construction of signed avatars, generates improved results, and allows for a more intuitive workflow for the artists and animators who interact with the system.} } @inproceedings{mcdonald:70003:sltat:lrec, author = {McDonald, John C. and Johnson, Ronan and Wolfe, Rosalee}, title = {A Novel Approach to Managing Lower Face Complexity in Signing Avatars}, pages = {67--72}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and McDonald, John C. and Shterionov, Dimitar and Wolfe, Rosalee}, booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {24}, month = jun, year = {2022}, isbn = {979-10-95546-82-5}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/2022.sltat-1.10.html}, doi = {10.63317/4m44kcfpe4cu}, abstract = {An avatar that produces legible, easy-to-understand signing is one of the essential components to an effective automatic signed/spoken translation system. Facial nonmanual signals are essential to natural signing, but unfortunately signing avatars still do not produce acceptable facial expressions, particularly on the lower face. This paper reports on an innovative method to create more realistic lip postures. The approach manages the complexity of creating lip postures, thus making fewer demands on the artists making them. The method will be integral to our efforts to develop libraries containing lip postures to support the generation of facial expressions for several sign languages.} } @inproceedings{wolfe:70005:sltat:lrec, author = {Wolfe, Rosalee and McDonald, John C. and Johnson, Ronan and Sturr, Ben and Klinghoffer, Syd and Bonzani, Anthony and Alexander, Andrew and Barnekow, Nicole}, title = {Supporting Mouthing in Signed Languages: New innovations and a proposal for future corpus building}, pages = {125--130}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and McDonald, John C. and Shterionov, Dimitar and Wolfe, Rosalee}, booktitle = {Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives}, maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {24}, month = jun, year = {2022}, isbn = {979-10-95546-82-5}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/2022.sltat-1.19.html}, doi = {10.63317/59xakmcizypn}, abstract = {A recurring concern, oft repeated, regarding the quality of signing avatars is the lack of proper facial movements, particularly in actions that involve mouthing. An analysis uncovered three challenges contributing to the problem. The first is a difficulty in devising an algorithmic strategy for generating mouthing due to the rich variety of mouthings in sign language. For example, part or all of a spoken word may be mouthed depending on the sign language, the syllabic structure of the mouthed word, as well as the register of address and discourse setting. The second challenge was technological. Previous efforts to create avatar mouthing have failed to model the timing present in mouthing or have failed to properly model the mouth's appearance. The third challenge is one of usability. Previous editing systems, when they existed, were time-consuming to use. This paper describes efforts to improve avatar mouthing by addressing these challenges, resulting in a new approach for mouthing animation. The paper concludes by proposing an experiment in corpus building using the new approach.} } @inproceedings{filhol:20015:sign-lang:lrec, author = {Filhol, Michael and McDonald, John C.}, title = {The Synthesis of Complex Shape Deployments in Sign Language}, pages = {61--68}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna}, booktitle = {Proceedings of the {LREC2020} 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives}, maintitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {16}, month = may, year = {2020}, isbn = {979-10-95546-54-2}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/20015.html}, doi = {10.63317/4rxzbmw8i78z}, abstract = {Proform constructs such as classifier predicates and size and shape specifiers are essential elements of Sign Language communication, but have remained a challenge for synthesis due to their highly variable nature. In contrast to frozen signs, which may be pre-animated or recorded, their variability necessitates a new approach both to their linguistic description and to their synthesis in animation. Though the specification and animation of classifier predicates was covered in previous works, size and shape specifiers have to this date remain unaddressed. This paper presents an efficient method for linguistically describing such specifiers using a small number of rules that cover a large range of possible constructs. It continues to show that with a small number of services in a signing avatar, these descriptions can be synthesized in a natural way that captures the essential gestural actions while also including the subtleties of human motion that make the signing legible.} } @inproceedings{johnson:20019:sign-lang:lrec, author = {Johnson, Ronan and Wolfe, Rosalee}, title = {A survey of Shading Techniques for Facial Deformations on Sign Language Avatars}, pages = {107--112}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna}, booktitle = {Proceedings of the {LREC2020} 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives}, maintitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {16}, month = may, year = {2020}, isbn = {979-10-95546-54-2}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/20019.html}, doi = {10.63317/52pbfwcyy5b5}, abstract = {Of the five phonemic parameters in sign language (handshape, location, palm orientation, movement and nonmanual expressions), the one that still poses the most challenges for effective avatar display is nonmanual signals. Facial nonmanual signals carry a rich combination of linguistic and pragmatic information, but current techniques have yet to portray these in a satisfactory manner. Due to the complexity of facial movements, additional considerations must be taken into account for rendering in real time. Of particular interest is the shading areas of facial deformations to improve legibility. In contrast to more physically-based, compute-intensive techniques that more closely mimic nature, we propose using a simple, classic, Phong illumination model with a dynamically modified layered texture. To localize and control the desired shading, we utilize an opacity channel within the texture. The new approach, when applied to our avatar ``Paula'', results in much quicker render times than more sophisticated, computationally intensive techniques.} } @inproceedings{moncrief:20018:sign-lang:lrec, author = {Moncrief, Robyn}, title = {Extending a Model for Animating Adverbs of Manner in {American} {Sign} {Language}}, pages = {151--156}, editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna}, booktitle = {Proceedings of the {LREC2020} 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives}, maintitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Marseille, France}, day = {16}, month = may, year = {2020}, isbn = {979-10-95546-54-2}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/20018.html}, doi = {10.63317/3zzo3djnjkej}, abstract = {The goal of this work is to show that a model produced to characterize adverbs of manner can be applied to a variety of neutral animated signs to be used towards avatar sign language synthesis. This case study presents the extension of a new approach that was first presented at SLTAT 2019 in Hamburg for modeling language processes that manifest themselves as modifications to the manual channel. This work discusses additions to the model to be effective for one-handed and two-handed signs, repeating and non-repeating signs, and signs with contact.} } @inproceedings{filhol:18024:sign-lang:lrec, author = {Filhol, Michael and McDonald, John C.}, title = {Extending the {AZee-Paula} Shortcuts to Enable Natural Proform Synthesis}, pages = {45--52}, editor = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka}, booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community}, maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Miyazaki, Japan}, day = {12}, month = may, year = {2018}, isbn = {979-10-95546-01-6}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18024.html}, abstract = {Proform structures such as classifier predicates have traditionally challenged Sign Language (SL) synthesis systems, particularly in respect to the production of smooth natural motion. To address this issue a synthesizer must necessarily leverage a structured linguistic model for such constructs to specify the linguistic constraints, and also an animation system that is able to provide natural avatar motion within the confines of those constraints. The proposed system bridges two existing technologies, taking advantage of the ability of AZee to encode both the form and functional linguistic aspects of the proform movements and on the Paula avatar system to provide convincing human motion. The system extends a previous principle that more natural motion arises from leveraging knowledge of larger structures in the linguistic description.} } @inproceedings{wolfe:18023:sign-lang:lrec, author = {Wolfe, Rosalee and Hanke, Thomas and Langer, Gabriele and Jahn, Elena and Worseck, Satu and Bleicken, Julian and McDonald, John C. and Johnson, Sarah}, title = {Exploring Localization for Mouthings in Sign Language Avatars}, pages = {207--212}, editor = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka}, booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community}, maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Miyazaki, Japan}, day = {12}, month = may, year = {2018}, isbn = {979-10-95546-01-6}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18023.html}, abstract = {According to the World Wide Web Consortium (W3C), localization is ``the adaptation of a product, application or document content to meet the language, cultural and other requirements of a specific target market''. One requirement necessary for localizing a sign language avatar is creating a capability to produce convincing mouthing. For purposes of this inquiry we make a distinction between mouthings and mouth gesture. The term `mouthings' refers to mouth movements derived from words of a spoken language whereas `mouth gesture' refers to mouth movements not derived from a spoken language. This effort focuses on the former. The prevalence of mouthings varies across different sign languages and individual signers. Although mouthings occur regularly in most sign languages, their significance and status have been a matter of sometimes heated discussions among sign linguists. However, no matter the theoretical viewpoint one takes on the issue of mouthing, one must acknowledge that for most if not all sign languages, mouthings do occur. If an avatar purports to fully and naturally express any sign language, it must have the capacity to express all aspects of the language, which likely will include mouthings. Although most avatar systems were created for hearing communities, several technologies have emerged to improve speech recognition for those who are hard-of-hearing or who find themselves in noisy environments. These were not satisfactory for Deaf communities as they did not portray sign language. Initial efforts to incorporate mouthing in sign language avatars utilized a mouth picture or viseme for each letter of the International Phonetic Alphabet (IPA), but were hampered by a reliance on blend shapes. Muscle-based avatars have the advantage of avoiding the limitations of blend shapes. This paper reports on a first step to identify the requirements for extending a muscle-based avatar to incorporate mouthings in multiple sign languages.} } @inproceedings{wolfe-etal-2014-expanding:lrec, author = {Wolfe, Rosalee and McDonald, John C. and Berke, Larwan and Stumbo, Marie}, title = {Expanding n-gram analytics in {ELAN} and a case study for sign synthesis}, pages = {1880--1885}, editor = {Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Loftsson, Hrafn and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios,}, booktitle = {9th International Conference on Language Resources and Evaluation ({LREC} 2014)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Reykjavik, Iceland}, day = {26--31}, month = may, year = {2014}, isbn = {978-2-9517408-8-4}, language = {english}, url = {https://aclanthology.org/L14-1484}, doi = {10.63317/4mfef8xvv55v}, abstract = {Corpus analysis is a powerful tool for signed language synthesis. A new extension to ELAN offers expanded n-gram analysis tools including improved search capabilities and an extensive library of statistical measures of association for n-grams. Uncovering and exploring coarticulatory timing effects via corpus analysis requires n-gram analysis to discover the most frequently occurring bigrams. This paper presents an overview of the new tools and a case study in American Sign Language synthesis that exploits these capabilities for computing more natural timing in generated sentences. The new extension provides a time-saving convenience for language researchers using ELAN.} } @inproceedings{schnepp:10007:sign-lang:lrec, author = {Schnepp, Jerry and Wolfe, Rosalee and McDonald, John C.}, title = {Synthetic Corpora: A Synergy of Linguistics and Computer Animation}, pages = {217--220}, editor = {Dreuw, Philippe and Efthimiou, Eleni and Hanke, Thomas and Johnston, Trevor and Mart{\'i}nez Ruiz, Gregorio and Schembri, Adam}, booktitle = {Proceedings of the {LREC2010} 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies}, maintitle = {7th International Conference on Language Resources and Evaluation ({LREC} 2010)}, publisher = {{European Language Resources Association (ELRA)}}, address = {Valletta, Malta}, day = {22--23}, month = may, year = {2010}, language = {english}, url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/10007.html}, abstract = {Synthetic corpora are computer representations of linguistic phenomena. They enable the creation of computer-generated animations depicting sign languages and are the complement of corpora containing videotaped exemplars. \par Synthetic corpora have the potential to serve multiple disciplines. They can aid in the automatic recognition of sign, because they contain the geometric data required for intelligent visual detection algorithms. Synthetic corpora can also provide visual depictions of abstract representations and act as a verification tool for data integrity and hypothesis testing. \par Because the signs are synthesized, not retrieved, they can be modified as they are formed. This provides the flexibility to generate an endless variety of utterances not possible with recordings, thus opening possibilities for automatic translation efforts. While representing sign for this purpose is still an open question, a synthetic corpus has the potential to serve in this capacity. The flexibility of synthetically-generated sign is also useful for the development of interpreter training software and self-directed learning tools for deaf children. \par By necessity, linguistics and computer animation must play a role in the creation of such corpora, as any corpus will need to serve both disciplines. At first glance, the goals of these disciplines would appear to be at cross purposes. Linguistics researchers often use corpora to form hypotheses through queries on linguistic features. Thus the corpora must encode such general abstractions as handshape, position, motion, palm orientation and non-manual signals. In contrast, creating computer animations of sign requires voluminous and detailed data, as the resulting animations must be realistic enough to pass the scrutiny of fluent signers. \par In actuality, the fields of linguistics and computer animation create a mutually beneficial synergy. Having the detailed precision required for animation can facilitate the exploration of subtle interactions among linguistic phenomena. Likewise, animators need an abstract representation to organize, combine, and synthesize complex animation data. \par Regardless of the animation technique, linguistic knowledge is necessary to produce any synthetic corpus. Animators who hand-transcribe need to work closely with linguists, so that the gloss is tagged correctly. Linguistic information guides the transcription artist's efforts to produce a natural exemplar that encapsulates the essential motions of a sign. With motion capture, the role of linguistics is no less central. Motion capture equipment generates massive amounts of data that must be cleaned to remove extraneous noise. The linguistic attributes of a sign give the cleanup artists precisely what they need to process and extract the desired motion. \par Our work thus far has focused on the creation of detailed and accurate animations of sign. The data that drive these animations have similarities to abstractions created by linguists. Thus, linguistic research guides the creation of a framework for automated sign synthesis. \par This presentation will examine several linguistic processes and discuss an approach to their representation in a synthetic corpus, including co-occurrence in nonmanual signals. This will include a demonstration of computer-generated American Sign Language.} }