@inproceedings{caminero:12014:sign-lang:lrec,
  author    = {Caminero, Javier and Rodriguez-Gancedo, Mari Carmen and Hernandez-Trapote, Alvaro and Lopez-Mencia, Beatriz},
  title     = {{SIGNSPEAK} Project Tools: A way to improve the communication bridge between signer and hearing communities},
  pages     = {1--6},
  editor    = {Crasborn, Onno and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Kristoffersen, Jette and Mesch, Johanna},
  booktitle = {Proceedings of the {LREC2012} 5th Workshop on the Representation and Processing of Sign Languages: Interactions between Corpus and Lexicon},
  maintitle = {8th International Conference on Language Resources and Evaluation ({LREC} 2012)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Istanbul, Turkey},
  day       = {27},
  month     = may,
  year      = {2012},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/12014.html},
  abstract  = {The SIGNSPEAK project is aimed at developing a novel scientific approach for improving the communication between signer and hearing communities. In this way, SIGNSPEAK technology captures the video information from the signer and converts it into text. To do that, SIGNSPEAK consortium has devoted great efforts to the creation and annotation of the RWTH-Phoenix corpus. Based on it, a multimodal processing of the captured video is carried out and the resultant sign sequence is translated into natural language. Afterwards, the intended message could be communicated to hearing-able people using a text-to-speech (TTS) engine. In the reverse way, speech from hearing-able people would be transformed into text using Automatic Speech Recognition (ASR) and then the text would be processed by virtual avatars able to compose the suitable sign sequence. In SIGNSPEAK project, scientific and usability approaches have been combined to go beyond the state-of-the-art and contributing to suppress barriers between signer and hearing communities. In this work, a special stress was put in the development of a prototype and also, in setting of the grounds for future real industrial applications.}
}

@inproceedings{forster-etal-2012-rwth:lrec,
  author    = {Forster, Jens and Schmidt, Christoph and Hoyoux, Thomas and Koller, Oscar and Zelle, Uwe and Piater, Justus and Ney, Hermann},
  title     = {{RWTH}-{PHOENIX}-{Weather}: A Large Vocabulary Sign Language Recognition and Translation Corpus},
  pages     = {3785--3789},
  editor    = {Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Do{\u g}an, Mehmet U{\u g}ur and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
  booktitle = {8th International Conference on Language Resources and Evaluation ({LREC} 2012)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Istanbul, Turkey},
  day       = {21--27},
  month     = may,
  year      = {2012},
  isbn      = {978-2-9517408-7-7},
  language  = {english},
  url       = {https://aclanthology.org/L12-1503},
  abstract  = {This paper introduces the RWTH-PHOENIX-Weather corpus, a video-based, large vocabulary corpus of German Sign Language suitable for statistical sign language recognition and translation. In contrastto most available sign language data collections, the RWTH-PHOENIX-Weather corpus has not been recorded for linguistic research but for the use in statistical pattern recognition. The corpus contains weather forecasts recorded from German public TV which are manually annotated using glosses distinguishing sign variants, and time boundaries have been marked on the sentence and the gloss level. Further, the spoken German weather forecast has been transcribed in a semi-automatic fashion using a state-of-the-art automatic speech recognition system. Moreover, an additional translation of the glosses into spoken German has been created to capture allowable translation variability. In addition to the corpus, experimental baseline results for hand and head tracking, statistical sign language recognition and translation are presented.}
}

@inproceedings{dreuw:10001:sign-lang:lrec,
  author    = {Dreuw, Philippe and Forster, Jens and Gweth, Yannick and Stein, Daniel and Ney, Hermann and Mart{\'i}nez Ruiz, Gregorio and Verges Llahi, Jaume and Crasborn, Onno and Ormel, Ellen and Du, Wei and Hoyoux, Thomas and Piater, Justus and Moya Lazaro, Jos{\'e} Miguel and Wheatley, Mark},
  title     = {{SignSpeak} - Understanding, Recognition, and Translation of Sign Languages},
  pages     = {65--72},
  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/10001.html},
  abstract  = {The SignSpeak project will be the first step to approach sign language recognition and translation at a scientific level already reached in similar research fields such as automatic speech recognition or statistical machine translation of spoken languages. Deaf communities revolve around sign languages as they are their natural means of communication. Although deaf, hard of hearing and hearing signers can communicate without problems amongst themselves, there is a serious challenge for the deaf community in trying to integrate into educational, social and work environments. The overall goal of SignSpeak is to develop a new vision-based technology for recognizing and translating continuous sign language to text. New knowledge about the nature of sign language structure from the perspective of machine recognition of continuous sign language will allow a subsequent breakthrough in the development of a new vision-based technology for continuous sign language recognition and translation. Existing and new publicly available corpora will be used to evaluate the research progress throughout the whole project.}
}

@inproceedings{forster:10038:sign-lang:lrec,
  author    = {Forster, Jens and Stein, Daniel and Ormel, Ellen and Crasborn, Onno and Ney, Hermann},
  title     = {Best Practice for Sign Language Data Collections Regarding the Needs of Data-Driven Recognition and Translation},
  pages     = {92--97},
  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/10038.html},
  abstract  = {We propose best practices for gloss annotation of sign languages taking into account the needs of data-driven approaches to recognition and translation of natural languages. Furthermore, we provide reference numbers for several technical aspects for the creation of new sign language data collections. Most available sign language data collections are of limited use to data-driven approaches, because they focus on rare sign language phenomena, or lack machine readable annotation schemes. Using a natural language processing point of view, we briefly discuss several sign language data collection, propose best practices for gloss annotation stemming from experience gained using two large scale sign language data collections, and derive reference numbers for several technical aspects from standard benchmark data collections for speech recognition and translation.}
}

@inproceedings{piater:10052:sign-lang:lrec,
  author    = {Piater, Justus and Hoyoux, Thomas and Du, Wei},
  title     = {Video Analysis for Continuous Sign Language Recognition},
  pages     = {192--195},
  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/10052.html},
  abstract  = {The recognition of continuous, natural signing is very challenging due to the multimodal nature of the visual cues (fingers, lips, facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues.  On the other hand, signing gestures are designed to be robustly discernible. We therefore argue in favor of an integrative approach to sign language recognition that aims to extract sufficient aggregate information for robust sign language recognition, even if many of the individual cues are unreliable.  Our strategy to implement such an integrated system currently rests on two modules, for which we will show initial results. The first module uses active appearance models for detailed face tracking, allowing the quantification of facial expressions such as mouth and eye aperture and eyebrow raise. The second module is dedicated to hand tracking using color and appearance.  A third module will be concerned with tracking upper-body articulated pose, linking the face to the hands for increased overall robustness.}
}

@inproceedings{serrano:10051:sign-lang:lrec,
  author    = {Serrano, Marina and Gumiel, Jes{\'u}s and Moya Lazaro, Jos{\'e} Miguel},
  title     = {Automatic sign language recognition, translation: a social approach},
  pages     = {221--224},
  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/10051.html},
  abstract  = {This paper reviews the social needs of the deaf community and describes the mechanisms and/or technologies which would improve the quality of life of this collective. The base of this project is a pilot of teleinterpretation developed in Andalusia (Spain), and as results of the interaction with the users, have been found two investigation lines, the telephone communication, and the e-learning. This activities have a clearly defined technology needs by hearing impaired, and the existing solutions do not fix completely the problem, so they are a good scenario to implement an automatic sing language recognition system. The aim of the paper is demonstrate how to thanks to this technology, social barriers can be torn down, allowing equal access to those services that today are restrictive for the collective of deaf people.}
}

@inproceedings{dreuw-etal-2010-signspeak:lrec,
  author    = {Dreuw, Philippe and Ney, Hermann and Mart{\'i}nez Ruiz, Gregorio and Crasborn, Onno and Piater, Justus and Moya Lazaro, Jos{\'e} Miguel and Wheatley, Mark},
  title     = {The {SignSpeak} Project - Bridging the Gap Between Signers and Speakers},
  pages     = {476--481},
  editor    = {Calzolari, Nicoletta and Choukri, Khalid and Maegaard, Bente and Mariani, Joseph and Odijk, Jan and Piperidis, Stelios and Rosner, Mike and Tapias, Daniel},
  booktitle = {7th International Conference on Language Resources and Evaluation ({LREC} 2010)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Valletta, Malta},
  day       = {17--23},
  month     = may,
  year      = {2010},
  isbn      = {978-2-9517408-6-0},
  language  = {english},
  url       = {https://aclanthology.org/L10-1238},
  abstract  = {The SignSpeak project will be the first step to approach sign language recognition and translation at a scientific level already reached in similar research fields such as automatic speech recognition or statistical machine translation of spoken languages. Deaf communities revolve around sign languages as they are their natural means of communication. Although deaf, hard of hearing and hearing signers can communicate without problems amongst themselves, there is a serious challenge for the deaf community in trying to integrate into educational, social and work environments. The overall goal of SignSpeak is to develop a new vision-based technology for recognizing and translating continuous sign language to text. New knowledge about the nature of sign language structure from the perspective of machine recognition of continuous sign language will allow a subsequent breakthrough in the development of a new vision-based technology for continuous sign language recognition and translation. Existing and new publicly available corpora will be used to evaluate the research progress throughout the whole project.}
}