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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8 Hits 41 – 60 of 157 41 Google Colab notebook ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 42 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 43 Local Sequence Alignment Experiment (3) ... Gagniuc, Paul A.. - : figshare, 2022 BASE Show details 44 Google Colab notebook ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 45 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 46 NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ... Gordon, Colin S.. - : figshare, 2022 BASE Show details 47 NLPropTest: Parsing English to Property-Based Tests with Categorial Grammars ... Gordon, Colin S.. - : figshare, 2022 BASE Show details 48 Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Mamidi, Radhika; Pant, Kartikey. - : Underline Science Inc., 2022 BASE Show details 49 Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hou, Yifan; Sachan, Mrinmaya. - : Underline Science Inc., 2022 BASE Show details 50 Pemanfaatan Bank-data Digital Dwibahasa dalam Kajian Terjemahan: Studi kasus padanan bahasa Indonesia untuk verba sinonim bahasa Inggris ROB & STEAL ... Rajeg, Gede Primahadi Wijaya; Rajeg, I Made; Kartini, Putu Dea Indah. - : figshare, 2022 BASE Show details 51 Pemanfaatan Bank-data Digital Dwibahasa dalam Kajian Terjemahan: Studi kasus padanan bahasa Indonesia untuk verba sinonim bahasa Inggris ROB & STEAL ... Rajeg, Gede Primahadi Wijaya; Rajeg, I Made; Kartini, Putu Dea Indah. - : figshare, 2022 BASE Show details 52 Chances and Challenges for Quantitative Approaches in Chinese Historical Phonology ... List, Johann-Mattis. - : Humanities Commons, 2022 BASE Show details 53 Computational Approaches to Historical Language Comparison ... List, Johann-Mattis. - : Humanities Commons, 2022 BASE Show details 54 The glyph project: The distinctiveness of written characters — online crowdsourcing for a typology of letter shapes ... Morin, Olivier. - : Open Science Framework, 2022 BASE Show details 55 Backchannel Behavior Influences the Perceived Personality of Human and Artificial Communication Partners Swerts, Marc; Blomsma, Peter; Skantze, Gabriel. - : KTH, Tal, musik och hörsel, TMH, 2022. : Tilburg University, 2022. : Frontiers Media SA, 2022 BASE Show details 56 Found speech and humans in the loop : Ways to gain insight into large quantities of speech Fallgren, Per. - : KTH, Tal-kommunikation, 2022 BASE Show details 57 Is a Wizard-of-Oz Required for Robot-Led Conversation Practice in a Second Language? Águas Lopes, José David; Cumbal, Ronald; Engwall, Olov. - : KTH, Tal-kommunikation, 2022. : KTH, Tal, musik och hörsel, TMH, 2022. : Springer Nature, 2022 Abstract: The large majority of previous work on human-robot conversations in a second language has been performed with a human wizard-of-Oz. The reasons are that automatic speech recognition of non-native conversational speech is considered to be unreliable and that the dialogue management task of selecting robot utterances that are adequate at a given turn is complex in social conversations. This study therefore investigates if robot-led conversation practice in a second language with pairs of adult learners could potentially be managed by an autonomous robot. We first investigate how correct and understandable transcriptions of second language learner utterances are when made by a state-of-the-art speech recogniser. We find both a relatively high word error rate (41%) and that a substantial share (42%) of the utterances are judged to be incomprehensible or only partially understandable by a human reader. We then evaluate how adequate the robot utterance selection is, when performed manually based on the speech recognition transcriptions or autonomously using (a) predefined sequences of robot utterances, (b) a general state-of-the-art language model that selects utterances based on learner input or the preceding robot utterance, or (c) a custom-made statistical method that is trained on observations of the wizard’s choices in previous conversations. It is shown that adequate or at least acceptable robot utterances are selected by the human wizard in most cases (96%), even though the ASR transcriptions have a high word error rate. Further, the custom-made statistical method performs as well as manual selection of robot utterances based on ASR transcriptions. It was also found that the interaction strategy that the robot employed, which differed regarding how much the robot maintained the initiative in the conversation and if the focus of the conversation was on the robot or the learners, had marginal effects on the word error rate and understandability of the transcriptions but larger effects on the adequateness of the utterance selection. Autonomous robot-led conversations may hence work better with some robot interaction strategies. ; QC 20220112 Keyword: Conversational practice; Dialogue management for spoken human-robot interaction; Language Technology (Computational Linguistics); Non-native speech recognition; Robot-assisted language learning; Språkteknologi (språkvetenskaplig databehandling) URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306942 https://doi.org/10.1007/s12369-021-00849-8 BASE Hide details 58 Using Machine Learning for Pharmacovigilance: A Systematic Review Patrick Pilipiec; Marcus Liwicki; András Bota In: Pharmaceutics; Volume 14; Issue 2; Pages: 266 (2022) BASE Show details 59 Vec2Dynamics: A Temporal Word Embedding Approach to Exploring the Dynamics of Scientific Keywords—Machine Learning as a Case Study Amna Dridi; Mohamed Medhat Gaber; Raja Muhammad Atif Azad; Jagdev Bhogal In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 21 (2022) BASE Show details 60 Правила генерации глагольных словоформ для новописьменного варианта ливвиковского наречия ... Krizhanovskaya, Natalia; Novak, Irina. - : figshare, 2022 BASE Show details Page: 1 2 3 4 5 6 7 8

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