TY - CHAP A1 - Johannßen, Dirk A1 - Biemann, Chris A1 - Remus, Steffen A1 - Baumann, Timo A1 - Scheffer, David T1 - GermEval 2020 Task 1 on the Classification and Regression of Cognitive and Motivational style from Text T2 - Proceedings of the 5th SwissText & 16th KONVENS Joint Conference 2020 N2 - This paper describes the tasks, databases, baseline systems, and summarizes submissions and results for the GermEval 2020 Shared Task 1 on the Classification and Regression of Cognitive and Motivational Style from Text. This shared task is divided into two subtasks, a regression task, and a classification task. Subtask 1 asks participants to reproduce a ranking of students based on average aptitude indicators such as different high school grades and different IQ scores. The second subtask aims to classify so-called implicit motives, which are projective testing procedures that can reveal unconscious desires. Besides five implicit motives, the target labels of Subtask 2 also contain one of six levels that describe the type of self-regulation when acting out a motive, which makes this task a multiclass-classification with 30 target labels. 3 participants submitted multiple systems. Subtask 1 was solved (best r = .3701) mainly with non-neural systems and statistical language representations, submissions for Subtask 2 utilized neural approaches and word embeddings (best macro F1 = 70.40). Not only were the tasks solvable, analyses by the participants even showed connections to the implicit psychometrics theory and behavioral observations made by psychologists. This paper describes the tasks, databases, baseline systems, and summarizes submissions and results for the GermEval 2020 Shared Task 1 on the Classification and Regression of Cognitive and Motivational Style from Text. This shared task is divided into two subtasks, a regression task, and a classification task. Subtask 1 asks participants to reproduce a ranking of students based on average aptitude indicators such as different high school grades and different IQ scores. The second subtask aims to classify so-called implicit motives, which are projective testing procedures that can reveal unconscious desires. Besides five implicit motives, the target labels of Subtask 2 also contain one of six levels that describe the type of self-regulation when acting out a motive, which makes this task a multiclass-classification with 30 target labels. 3 participants submitted multiple systems. Subtask 1 was solved (best r =.3701) mainly with non-neural systems and statistical language representations, submissions for Subtask 2 utilized neural approaches and word embeddings (best macro F1 = 70.40). Not only were the tasks solvable, analyses by the participants even showed connections to the implicit psychometrics theory and behavioral observations made by psychologists. Y1 - 2020 UR - https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2020-johannssen-germeval20-1-companion-paper.pdf SP - 1 EP - 10 CY - Zurich, Switzerland ER - TY - CHAP A1 - Geislinger, Robert A1 - Milde, Benjamin A1 - Baumann, Timo A1 - Biemann, Chris T1 - Live Subtitling for BigBlueButton with Open-Source Software T2 - INTERSPEECH 2021: (Show & Tell Contribution), 30 August – 3 September, 2021, Brno, Czechia N2 - We present an open source plugin for live subtitling in the popular open source video conferencing software BigBlueBut-ton. Our plugin decodes each speaker’s audio stream separately and in parallel, thereby obliviating the need for speaker di-arization and seamlessly handling overlapped talk. Any Kaldi-compatible nnet3 model can be used with our plugin and we demonstrate it using freely available TDNN-HMM-based ASR models for English and German. Our subtitles can be used as they are (e.g., in loud environments) or can form the basis for further NLP processes. Our tool can also simplify the collection of remotely recorded multi-party dialogue corpora. KW - automatic speech recognition KW - automatic subtitles KW - computer-supported collaborative work KW - meeting transcription KW - multi-party dialogue KW - videoconferencing KW - VoIP Y1 - 2021 UR - https://www.isca-speech.org/archive/pdfs/interspeech_2021/geislinger21_interspeech.pdf SP - 3319 EP - 3320 CY - Brno, Czechia ER -