introduction to human language technology · speech recognition: hmm (khudanpur) deep learning...
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Introduction to Human Language Technology
Philipp Koehn
29 August 2019
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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1Administrative
• Coordinator: Philipp Koehn ([email protected])
• Lecturers: Faculty of the Center for Language and Speech Processing (CLSP)
• TA: Adi Renduchintala ([email protected])TA: Daniil Pakhomov ([email protected])
• Class: Monday, Wednesday, 3:00-4:15pm, Olin 305
• Course web site: https://jhu-intro-hlt.github.io/
• Grading– 5 assignments (10% each)– midterm exam (20%)– final exam (30%)
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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2Course Overview
• Human Language Technology
– Speech: spoken language (audio)– Text: written language (text)
• Means of Communication→ new ways of interacting with computers
• Storage medium for knowledge→ new ways of making word knowledge available
• This course
– methods and tools used in HLT– overview of HLT applications
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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3Course Overview: Speech
• Audio signals, phonemes, graphemes, dictionaries (Hermansky)
• Auditory system (Hermansky)
• Signal processing (Khudanpur)
• Speech recognition: HMM (Khudanpur)
• Deep learning (Watanabe)
• End-to-end neural speech recognition (Watanabe)
• Speaker identification, language identification (Dehak)
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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4Course Overview: Text
• Words, Morphology, Syntax
• Finite state toolkits
• Cognitive Psychology: memory, categories
• Semantics: embeddings, roles, frames, scripts
• Outsourcing linguistic data annotation
• Information retrieval and extraction
• Entity detection and tracking
• Text classification (topics, sentiment, relevance, ...)
• Machine translation
• Semantic entailment
• Question answering
• Dialog systems
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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5Master Concentration in HLT
https://www.clsp.jhu.edu/human-language-technology-masters/
• New this year: Concentration in Human Language Technology
– Master in Computer Science– Master in Electrical and Computer Engineering
• Requirements (in addition to usual degree requirements)
– Introduction to Human Language Technology (601.667)– Natural Language Processing (601.665)– Information Extraction from Speech and Text (520.666)– Master project in HLT
• Application forms at the end of this semester (including project selection)
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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6Center for Language and Speech Processing
• One of the largest and most influential academic research centers in HLT
• Faculty in Computer Science, Electrical and Computer Engineering, CognitiveScience, Mathematical Sciences, ...
• Home of over 60 researchers, dozens of PhD students
• Founded in 1992 by Frederick Jelinek (1932-2010)
• Sibling center: Human Language Technology Center of Excellence (HLTCOE)
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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7Speech Recognition
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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8Information Retrieval
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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9Information Extraction
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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10Machine Translation
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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11Question Answering
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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12Dialog Systems
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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13Hate Speech Detection
incitement of violence / dehumanizing individuals or groups of people
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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14Fake News Detection
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019
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15Common Themes
• Hard problems→ not solved, but good enough technology
• Common methods with other subfields of artificial intelligence
• Technology is advancing rapidly
• New applications on (and just behind) horizon
Philipp Koehn Introduction to Human Language Technology: Introduction 29 August 2019