418 results on '"Julia Hirschberg"'
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2. Using Adaptive Empathetic Responses for Teaching English.
3. Measuring Entrainment in Spontaneous Code-switched Speech.
4. Multimodal Multi-loss Fusion Network for Sentiment Analysis.
5. TweetIntent@Crisis: A Dataset Revealing Narratives of Both Sides in the Russia-Ukraine Crisis.
6. DialGuide: Aligning Dialogue Model Behavior with Developer Guidelines.
7. Capturing Formality in Speech Across Domains and Languages.
8. Human-AI Collaboration for the Detection of Deceptive Speech.
9. Identifying Entrainment in Task-Oriented Conversations.
10. CHoRaL: Collecting Humor Reaction Labels from Millions of Social Media Users.
11. Acoustic-Prosodic, Lexical and Demographic Cues to Persuasiveness in Competitive Debate Speeches.
12. 'Talk to me with left, right, and angles': Lexical entrainment in spoken Hebrew dialogue.
13. Identifying the Popularity and Persuasiveness of Right- and Left-Leaning Group Videos on Social Media.
14. Understanding How People Rate Their Conversations.
15. Detection of Mental Health from Reddit via Deep Contextualized Representations.
16. Multimodal Deception Detection Using Automatically Extracted Acoustic, Visual, and Lexical Features.
17. A Novel Methodology for Developing Automatic Harassment Classifiers for Twitter.
18. Subset Selection, Adaptation, Gemination and Prosody Prediction for Amharic Text-to-Speech Synthesis.
19. Prosody Prediction from Syntactic, Lexical, and Word Embedding Features.
20. Multimodal Indicators of Humor in Videos.
21. Sincerity in Acted Speech: Presenting the Sincere Apology Corpus and Results.
22. Improving Code-Switched Language Modeling Performance Using Cognate Features.
23. Linguistically-Informed Training of Acoustic Word Embeddings for Low-Resource Languages.
24. Predicting Humor by Learning from Time-Aligned Comments.
25. Crowdsourced Hedge Term Disambiguation.
26. Exploring New Methods for Identifying False Information and the Intent Behind It on Social Media: COVID-19 Tweets.
27. La fundación de Puebla de los Ángeles - Mito y realidad
28. Predicting Arousal and Valence from Waveforms and Spectrograms Using Deep Neural Networks.
29. The Role of Cognate Words, POS Tags and Entrainment in Code-Switching.
30. Acoustic-Prosodic Indicators of Deception and Trust in Interview Dialogues.
31. A Comparison of Speaker-based and Utterance-based Data Selection for Text-to-Speech Synthesis.
32. Deep Personality Recognition for Deception Detection.
33. Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task.
34. Joint Part-of-Speech and Language ID Tagging for Code-Switched Data.
35. Linguistic Cues to Deception and Perceived Deception in Interview Dialogues.
36. Comparing Approaches for Automatic Question Identification.
37. Hybrid Acoustic-Lexical Deep Learning Approach for Deception Detection.
38. Utterance Selection for Optimizing Intelligibility of TTS Voices Trained on ASR Data.
39. Crowdsourcing Universal Part-of-Speech Tags for Code-Switching.
40. LieCatcher: Game Framework for Collecting Human Judgments of Deceptive Speech.
41. Incrementally Learning a Dependency Parser to Support Language Documentation in Field Linguistics.
42. Implementing Acoustic-Prosodic Entrainment in a Conversational Avatar.
43. Combining Acoustic-Prosodic, Lexical, and Phonotactic Features for Automatic Deception Detection.
44. Automatically Classifying Self-Rated Personality Scores from Speech.
45. Data Selection and Adaptation for Naturalness in HMM-Based Speech Synthesis.
46. The INTERSPEECH 2016 Computational Paralinguistics Challenge: Deception, Sincerity & Native Language.
47. Part of Speech Tagging for Code Switched Data.
48. Babler - Data Collection from the Web to Support Speech Recognition and Keyword Search.
49. Testing the consistency assumption: Pronunciation variant forced alignment in read and spontaneous speech synthesis.
50. Collecting Code-Switched Data from Social Media.
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