In syntax, verb-initial (V1) word order is a word order in which the verb appears before the subject and the object. In the more narrow sense, this term is used specifically to describe the word order of V1 languages (a V1 language being a language where the word order is obligatorily or predominantly verb-initial). V1 clauses only occur in V1 languages and other languages with a dominant V1 order displaying other properties that correlate with verb-initiality and that are crucial to many analyses of V1. V1 languages are estimated to make up 12–19% of the world’s languages. V1 languages constitute a diverse group from different language families. They include Berber, Biu-Mandara, Surmic, and Nilo-Saharan languages in Africa; Celtic languages in Europe; Mayan and Oto-Manguean languages in North and Central America; Salish, Wakashan, and Tsimshianic languages in North America; Arawakan languages in South America; Austronesian languages in Southeast Asia. Some languages are ordered strictly as verb-subject-object (VSO), for example Q’anjob’al (Mayan). Others are ordered strictly as verb–object–subject (VOS), for example Malagasy (Austronesian). Many alternate between VSO and VOS, an example being Ojibwe (Algonquian). (Wikipedia).
ATTRIBUTIVE and PREDICATE ADJECTIVES - ENGLISH GRAMMAR
We talk about adjectives: attributive and predicative. Attributive adjectives appear before the nouns they modify. Predicative adjectives appear after a BE or LINKING verb. If you want to support the channel, hit the "JOIN" button above and pick a channel subscription that suits your need
From playlist English Grammar
[Introduction to Linguistics] Word Order, Grammaticality, Word Classes
In this video we look at word order in languages, grammaticality, prescriptive and descriptive grammar, as well as go over functional categories and lexical categories. LIKE AND SHARE THE VIDEO IF IT HELPED! Support me on Patreon: http://bit.ly/2EUdAl3 Visit our website: http://bit.ly/1z
From playlist Introduction to Linguistics
SYN126 - Head Nouns - Noun Classes
In this first of two E-Lectures about head nouns in PDE, Prof. Handke discusses the grammatical and semantic criteria that keep different types of nouns and their function apart. As usual, numerous examples are used to support the central argumentation.
From playlist VLC201 - The Structure of English
NOUN PHRASES - ENGLISH GRAMMAR
We discuss noun phrases. Noun phrases consist of a head noun, proper name, or pronoun. Noun phrases can be modified by adjective phrases or other noun phrases. Noun phrases take determiners as specifiers. We also draw trees for noun phrase. you want to support the channel, hit the "JOIN"
From playlist English Grammar
SYN121 - The Verb in PDE - Part II
In this second of a series of three E-Lectures Prof. Handke discusses the distinction between lexical and auxiliary verbs using the NICE-criteria as well as additional morpho-syntactic criteria. This includes a distinction between primary and secondary auxiliary verbs.
From playlist VLC201 - The Structure of English
DEFINITE AND INDEFINITE ARTICLES - ENGLISH GRAMMAR
We discuss the indefinite articles a, an, and definite article the. 'the' is used when a noun exists and is unique. 'a' or 'an' is used for non-specific nouns. 'a' is used before words that start with a consonant sound. 'an' is used before words that start with a vowel sound. If you want
From playlist English Grammar
The syntactic classification of languages is by and large based on their word order. How do we establish the basic word order of a language and how additional head-modifier constructions may supplement the central ordering patterns constitutes the focus of this E-Lecture. A special feature
From playlist VLC108 - Language Typology
Mod-01 Lec-28 Syntax: An Introduction Cont…
Introduction to Modern Linguistics by Prof.Shreesh Chaudhary & Prof. Rajesh Kumar,Department of Humanities and Social Sciences,IIT Madras.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Madras: Introduction to Modern Linguistics | CosmoLearning.org English Language
MIT 24.900 Introduction to Linguistics, Spring 2022 Instructor: Prof. Norvin W. Richards View the complete course: https://ocw.mit.edu/courses/24-900-introduction-to-linguistics-spring-2022/ YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63BZGNOqrF2qf_yxOjuG35j This v
From playlist MIT 24.900 Introduction to Linguistics, Spring 2022
[Syntax] Nouns and Their Grammatical Properties
We introduce nouns and their grammatical properties, such as gender, class, number, nominative case, accusative case, genitive case. LIKE AND SHARE THE VIDEO IF IT HELPED! Visit our website: http://bit.ly/1zBPlvm Subscribe on YouTube: http://bit.ly/1vWiRxW Like us on Facebook: http://on.
From playlist Syntax
Template Based Information Extraction with Dendograms to Classify News Articles
Install NLP Libraries https://www.johnsnowlabs.com/install/ Register for Healthcare NLP Summit 2023: https://www.nlpsummit.org/#register Watch all NLP Summit 2022 sessions: https://www.nlpsummit.org/nlp-summit-2022-watch-now/ Presented by Daniel Svoboda, NLP Research Scientist at John
From playlist NLP Summit 2022
[Introduction to Linguistics] Word Creation
In this video, we look at Compounding, Clipping, Blending, Backformation, Acronyms, Initialisms, and Coinage as forms of word creation in English. LIKE AND SHARE THE VIDEO IF IT HELPED! Support me on Patreon: http://bit.ly/2EUdAl3 Visit our website: http://TrevTutor.com Subscribe on You
From playlist Introduction to Linguistics
Computational Linguistics I: Part of Speech Tagging
There's an error defining the transition matrix. It should be \theta_{i,j} = p(z_n = j | z_{n-1} = 1), not \beta.
From playlist Computational Linguistics I
Morpheme Based Model and Word Based Model | Morphology Linguistics
We introduce the word-based model and morpheme-based model with lexical entries, selectional restrictions, and meanings. We talk about affixation, compounding, backformation, internal change, vowel lengthening, suprafixes, duplifixes, partial reduplication, and reduplication. 0:00 Introdu
From playlist Morphology - Linguistics
R & Python - Parsing Part 1 (2022)
Lecturer: Dr. Erin M. Buchanan Spring 2022 https://www.patreon.com/statisticsofdoom This video is part of my Natural Language Processing course. This video covers parsing, which is creating sentence structure for understanding meaning. You will learn both traditional constituency parsing
From playlist Natural Language Processing
How to Estimate the Parameters of a Hidden Markov Model from Data [Lecture]
This is a single lecture from a course. If you you like the material and want more context (e.g., the lectures that came before), check out the whole course: https://boydgraber.org/teaching/CMSC_723/ (Including homeworks and reading.) Intro to HMMs: https://youtu.be/0gu1BDj5_Kg Music: h
From playlist Computational Linguistics I
[Syntax] Theta Roles and Theta Grids
We talk about semantics and introduce theta roles and theta grids. The roles we talk about are Agents, Themes, Experiencers, Goals, and Locations. LIKE AND SHARE THE VIDEO IF IT HELPED! Visit our website: http://bit.ly/1zBPlvm Subscribe on YouTube: http://bit.ly/1vWiRxW Like us on Facebo
From playlist Syntax
Lecture 11: Gated Recurrent Units and Further Topics in NMT
Lecture 11 provides a final look at gated recurrent units like GRUs/LSTMs followed by machine translation evaluation, dealing with large vocabulary output, and sub-word and character-based models. Also includes research highlight ""Lip reading sentences in the wild."" Key phrases: Seq2Seq
From playlist Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017)
"Appreciate that if different selections are independent, each with a number of choices, then the total number of combinations is the product of these."
From playlist Number: Combinations & Permutations
Lecture 8/16 : More recurrent neural networks
Neural Networks for Machine Learning by Geoffrey Hinton [Coursera 2013] 8A A brief overview of "Hessian-Free" optimization 8B Modeling character strings with multiplicative connections 8C Learning to predict the next character using HF 8D Echo state networks
From playlist Neural Networks for Machine Learning by Professor Geoffrey Hinton [Complete]