A list of puns related to "Analytic Language"
I was wondering if Wolof and Fula are analytic languages? I've not been able to find much information about their typology, especially in comparison to discussions of Yoruba (analytic) and Swahili (agglutinative).
EQ: Beyond Yoruba and closely related languages, what are the analytic languages in Africa?
"P't'h P't'k'p's" is a simplification of "f'f p't'h f'sh p't'k'p's", roughly "the sound(s) of speech" in my first Blang, short for Beatbox Conlang. Do I need to specify conlang? I know of no natural beat-box languages, but oh well.
Phonology & Syllable Structure
The phoneme inventory is simple, and it's meant to be. Beatboxing makes use of many sounds, and in far more complex patterns than this blang, but I aim to develop a bigger inventory for my next blang. The romanisation is in brackets where applicable, the rest is IPA. I realize the orthography is a bit ugly, happy to take alternative suggestions. Allophony is minimal, but x varies with h and Ο in realization, hence the romanisation I chose. There is also some alterations in the realization of sibilants, both affricates and sibilants, if they are tautosyllabic with another sibilant (that is to say, I can hear them sounding different when I am doing them, but I can't put my finger on how).
Labial | Denti-alveolar | Post-alveolar | Velar | |
---|---|---|---|---|
Ejective Stop | p' | t' | k' | |
Ejective Fricative/Affricate | f' | ts' | tΚ' (tsh') | |
Fricative | f | s | Κ (sh) | x (h) |
Syllable structure is highly restricted, every syllable ends in a fricative and can have up to 5 of the other consonants before it and must have at least 1. Treating fricatives as vowels, the syllable structure is C(C)(C)(C)(C)V, with the restriction that no two of the same consonant can occur in a row in roots, though this will occur after initial reduplication.
So the language is really [p't'x.p't'k'p's] ~ , [p't'h.p't'k'p's] two syllables, two syllabic fricatives as nuclei and two initial clusters of ejective stops.
The Main Bits
This language has a set of particles that I usually gloss as classifiers. They stand obligatorily in every noun and verb phrase. In verb phrases, they stand in SVO order. In noun phrases, most particles (prepositions, demonstratives, numerals, quantifiers) stand before the classifier, adjectives and then nouns after it. Adjectives can occur "stranded" away from their noun as they carry an agreeing classifier, and noun phrases can occur in any position around a verb phrase, usually following a topic prominent structure. Pronouns follow a similar distribution and can also stand just ahead of any other classifier as a possessive marker.
Here's a simple sentence as an example:
1st have CL.food CL.food meat
k's p'ts'sh k'p's k'p's p'k't'sh
I have it, it meat
This would properly translat
... keep reading on reddit β‘Hello, are there some examples of fusional languages moving to become more agglutinative or analytic languages becoming more fusional? If yes, what's the mechanism of that?
I generally know how it works in the other direction: distinct morphemes in agglutinative languages fuse into one when languages move from agglutinative to fusional, and distinction between inflections is lost in fusional languages necessitating use of auxiliaries and prepositions when languages move from fusional to analytic.
I am a beginner and have learned Python, Pandas, Excel and the Basics of Hypothesis Testing and wanted to know what should I learn and what certifications I should prepare for If I want to get a Career in Business Analytics or Data Analytics so please can anyone tell me what should I do and also what type of projects I should do?
What in your opinion is the best and/or most helpful computer programming language for someone who wants to be a data analytics professional?
In English, children often leave out certain types of words as they are learning to speak and forming sentences. For instance, they might say "I not" instead of "I don't" or "I won't", leaving out the supportive "do" or "will" verbs.
Entire words can be dropped without too much damage to the meaning of the phrase, because words are atomic units in English.
But I wonder, how does children's speech differ in languages where many units of meaning are compounded into a single word? If a child leaves out one word, that single word might cover what would be several parts of speech in English.
How is their speech simplified? Do they leave out morphological elements of compound words? Or is their speech "delayed" until they can properly form whole words with all requisite elements?
If you have examples in Finnish that would be wonderful, because I have some passing ability in Finnish.
I've spent the last two months reading through introductory books and classic articles within analytic philosophy of language, mostly relying on Martinich and Sosa's collection, The Philosophy of Language. This has left me with some knowledge of the field up to the mid 90s, but with little to no exposure to 21st century work.
Are there any issues that have been hot topics in recent years? Are there any which were popular at the turn of the century, but are now waning in popularity?
My reason for asking is that I'm planning to apply to MA programs for the Fall 2022 semester, and I'm looking to prepare writing samples. I'd like to make some attempt at being relevant and in conversation with recent work, but I'd also like to avoid topics that are seen as settled or that are only seen as significant by smaller factions within the discipline.
Are the debates on theories of reference (e.g., debates between descriptive/causal theories) still going strong? Is significant work still being done on speech act theory?
Any insight is appreciated!
hi reddit, i am thinking to move to Japan in 2022 to attend language school for a year under a student visa and then hopefully land a job.
work experience wise, I have about 5 years of experience in the BI/data field, 2 of those in senior level at a multinational ecommerce firm. I was hoping to get some opinions regarding this against the current market. Our typical job titles are data/business/business intelligence analyst and we use SQL, Tableau python etc. regarding education, i have a bachelors and a masters so I think i do not need 10 years of work exp to qualify for a work visa
language school-wise, can anyone share me recommendations for a school that works best for a foreign professional? most schools are geared towards students and so far the 2 schools that look the most enticing to me is Waseda and JASSO. But I'm still looking around
I privately teach philosophy to students whose second language is English, but whose analytic skills are very strong. Generally speaking, we are able to have great conversations and cover a lot of ground. But I find it quite difficult to find texts, where the writing is simple and clear enough for them to read. The primary text I use is Blackburn's 'Think'. Which covers introductory topics in a fairly simple way, but sometimes the language is too filled with (jargon aside) novel vocabulary, idioms and references that are just a bit too complex for the students.
Does anyone have any other recommendations for texts that would be suitable for someone with strong philosophical skills, but whose English is just a little shy of the level of language/writing style of 'Think'. I'd appreciate any recommendations on books, summaries of academic articles, or even academic articles written in relatively plain English.
I hear a lot about synthetic languages when every people talk about languages they find interesting, which I'm not complaining about okay because they can be really interesting. Especially how many things they can do, like languages with noun cases can have free word order, or how poly-synthetic languages can make an entire sentence into one long word.
I don't however hear much about analytic languages. Probably because this sub is full of primarily native English speakers and English is fairly analytic itself so analytic language features probably go overlooked. But still, I was wondering, are there any language features that analytic languages don't that either synthetic languages don't have or are much rarer among them?
Suppose there are two languages, A and B.
In order to remove the influence of other factors, suppose that they both have simple phonologies and almost zero vocabulary overlap with any of the languages you already speak.
A is analytic while B is inflecting.
Anecdotal evidence seems to suggest that you, as a L2/adult learner, will find language A to be easier to learn regardless of your native language or other languages that you speak.
Has anyone tried to investigate this formally?
Of course, all languages should be equally difficult to learn for a child learning their first language. But for adult learners specifically, it seems that in general, analytic languages are easier to learn inflecting languages. That is to say, if we were to calculate an abstracted "difficulty score" for any language you were to learn, then a language being analytic would automatically give it a -1.0 in terms of difficulty while a language being inflected would give it a +1.0 in terms of difficulty regardless of any other factors.
The fact that all creoles/pidgins (i.e. languages which started out with no native speakers) are analytic is perhaps evidence in favor of this?
Hey people,
Quick question. How much (and what kind) of programming is used in this program.
I see the SAS and SQL stuff, but are Python and R used at all?
I have a solid programming background (in addition to SQL) and I was wondering how much I will need to learn a new language/tool (SAS) vs. being able to use my existing Python knowledge to help me speed things up.
As a secondary question, what are the more programmatic projects or environments actually like?
For developers who are working on Deep learning based Video Analytics Projects, I would like to know what programming languages you use for a prototype development and for a production level solutions.
I'm a layman and I have no formal training in linguistics. I do know both an analytic language (if English counts) and an agglutinative one (though neither natively) and the following came to mind as I was thinking about agglutination.
I'll start off by saying that I'm not at all sold to the idea of the concept "word" being at all meaningful. I understand the concepts "morpheme", "phrase", and "clause" and to me they have rigorous and meaningful definitions to them. However, the concept "word" seems to float somewhere between the former two and I see no possibility to draw a hard line. Attempts to define the concept "word" and why they fail in my mind:
"That which is separated by spaces" - Language is speech; spaces, just like all writing, are an arbitrary human construct. This breaks down further considering languages with no spaces like Japanese.
"The smallest thing that can be used in isolation to convey meaning" - I'm not convinced that English "words" like "to" or "the" convey any meaning in isolation. This seems to be just as nonsensical as uttering some affixes of an agglutinative language in isolation. On the flipside, utterances like "m'm" ought to be words because they convey meaning used in isolation.
"That which can be reordered within a sentence" - That's a phrase.
Now on to agglutination: In absence of a universal definition of the concept "word", how can we distinguish between analytic and agglutinative languages? Common definitions seem to focus either on spelling, which is not an inherent quality of the language, or on words, which is an ill-defined concept (to the best of my understanding).
Wikipedia gives the following definition for agglutination: "Agglutination is a linguistic process pertaining to derivational morphology in which complex words are formed by stringing together morphemes without changing them in spelling or phonetics." This definition seems to me to be problematic in two different ways: Firstly the usage of "word" in absence of a universal definition of said concept, and moreover the dependence on spelling in light of the fact that spelling is an arbitrary human construct and a mere attempt to capture language. What I get from this definition is that agglutination is a derivational morphological process that operates "locally" ("without change in phonetics"). This definition seems utterly implausible to me; consider vowel harmony, consonant gradation, connec
... keep reading on reddit β‘Hi,
I'm setting up an Google Analytics account for a site with multiple languages. I want to set up different views per language.
I've tried doing this by adding this filter on View level:
Include only
traffic to the hostname
that begins with hostname (/en)
Unfortunately, this applies to all filters so I can't distinct multiple languages.
How could I separate multiple languages (based on domain.com/en etc.) in different views in Google Analytics?
Thanks!
I'm interested in AI and would like to work more with Salesforce Einstein features, Tableau, or Analytics. I'm interested in hearing what language people think I should invest time in if I'm interested in using/building those features/functionalities.
Amazon Textract, Amazon Comprehend, Azure Language Understanding, Azure Text Analytics, Azure Cognitive Search, Watson Natural Language Understanding, Watson Discovery, IBM Watson Knowledge Studio, Google Cloud Natural Language API...
Which of these services have you used (or other APIs)? What was the use case? If you tried multiple services, which worked best for your use case?
Hello, I have split the hubba github analytics gem into two, that is, hubba and hubba-reports for easier (re)use and split the data gathering / collecting via github api calls and the report generation. Anyways, I have added a new language report that lists all your languages used by char / bytes count and by number of repos. See LANGUAGES.md as an example. Happy data crunching with ruby. Cheers. Prost.
PS: Know any other alternative github scripts / gems, please tell.
A strong focus on correlations between theoretical linguistics and NLP. https://youtu.be/dMo_eLNsg08 | https://twitch.tv/wasspen - a new channel - cause sharing is caring π
How many of you are having to use programming languages like R and python and c++ as part of your job? Do you have to do machine learning related stuff also? What about preditive analytics? Has PA increased fun level of the work you people do?
I was curious because most Indo-european languages are losing things like dual number, declensions, etc. If the general trend is for languages to lose its declensions, how did PIE become so synthetic in the first place? Sorry if this is a dumb question, I'm a noob here.
English: Almost immediately shortens "coronavirus" to "corona"; later decides it's too vague and tries to switch to "covid-19". Also can't help but smash some words together, so people with inadequate reactions get called "covidiots". I'm pretty sure I'm missing some other neologisms, but these are pretty characteristic.
Russian: Also tries "ΠΊΠΎΡΠΎΠ½Π°" but the word is already being used for "a crown". After some hesitation it stumbles upon the tansliteration "ΠΊΠΎΠ²ΠΈΠ΄", deems it worthy to be a noun and a stem, and in just a few weeks there are 90k google results for the adjective "ΠΊΠΎΠ²ΠΈΠ΄Π½ΡΠΉ" (...ΠΊΠ°ΡΠ΅Π»Ρ, Π³ΠΎΡΠΏΠΈΡΠ°Π»Ρ, ΠΏΠ°ΡΠΈΠ΅Π½Ρ, etc), including official speeches (!). Meanwhile folks derive another adjective "ΠΊΠΎΠ²ΠΈΠ΄Π½ΡΡΡΠΉ" which might mean either a covidiot or someone who's ill and the speaker feels strongly negative about it.
Perfect example of how languages work in general :)
I've spent the last two months reading through introductory books and classic articles within analytic philosophy of language, mostly relying on Martinich and Sosa's collection, The Philosophy of Language. This has left me with some knowledge of the field up to the mid 90s, but with little to no exposure to 21st century work.
Are there any issues that have been hot topics in recent years? Are there any which were popular at the turn of the century, but are now waning?
My reason for asking is that I'm planning to apply to MA programs for the Fall 2022 semester, and I'm looking to prepare writing samples. I'd like to make some attempt at being relevant and in conversation with recent work, but I'd also like to avoid topics that are seen as settled or that are only seen as significant by smaller factions within the discipline.
Are the debates on theories of reference (e.g., debates between descriptive/causal) still going strong? Is significant work still being done on speech act theory?
Any insight is appreciated!
A strong focus on correlations between theoretical linguistics and NLP.YouTube |Twitch Link - a new channel - cause sharing is caring π
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