Monthly Archives: February 2013

Corpus Linguistics (Alan Du, 2/26/13)

TOPICS (thanks to Megan): Analysis of corpora with Python, frequency and ranking of words, Allometric Scaling Laws, Zipf’s and Mandelbrot’s laws, Hapax Legomena, and the transition from empirical linguistics to rationalism (via Chomsky).

Corpus is any body of language (think corpse). There are many different types of corpora, but we focused mainly on text corpora. Usually, text corpora comes with pre-parsed text – the text has already been split up into paragraphs, sentences, and words in a process called tokenization. Of course, there’s some controversy here. For example, are collocations like New York one word or two words? What about database vs database? What about blue-green?

Some corpora also come with part-of-speech (POS) tagging of each word. Some really nice corpora even come with the syntactic structure of the sentence. Good corpora can be great resources for all kinds of things, from testing hypotheses about language to training data for NLP.

Choosing your corpus matters. Corpora that come from joke books will be significantly different from those that come from editorials. I gave a small demonstration using the Brown corpus and generating 100 words of editorial text vs religious text:

Editorial Religon
Assembly session brought much good The General Assembly shall consider and approve the budget of the Organization shall be borne by the Members as apportioned by the General Assembly decided to tackle executive powers . The final decision went to the executive but a way has been opened for strengthening budgeting procedures and to provide legislators information they need . Long-range planning of programs and ways to finance them have become musts if the state in the next few years . The I. A. P. A. found itself driven from journalism into politics as it did its best to bring As a result , although we still make use of the pax-ordo of the earthly city and acknowledge their share in responsibility for its preservation . Not to repel injury and to preserve any particular civilized attainment of mankind or its provisional justice runs some risk of nuclear war ” . If we are born of God we overcome the world . In fact , during the burning of the vast Ch’in palace some ten years later ; ; yet he did not stop being human as a result of the Civil War , emancipation was achieved . Long before

To generate the text, I basically counted 4-grams (set of 4 words), and then randomly generated the next word based on the previous three, using the counts to determine respective probabilities. As you can tell, there are some obvious problems with this. But it’s also amazing that we can do this well just be counting sets of 4 words.

from nltk.corpus import brown
from nltk.probability import MLEProbDist
from nltk.model import NgramModel

est = lambda fdist, bins: MLEProbDist(fdist)
edit = NgramModel(4, brown.words(categories='editorial'), estimator=est)
relig = NgramModel(4, brown.words(categories='religion'), estimator=est)

print ' '.join(edit.generate(100))
print ' '.join(relig.generate(100))

Scaling Laws
In biology, there are some allometric scaling laws. For example: heart beat = k * mass^{\frac{3}{4}}

Zipf's Law for the Brown Corpus
Zipf’s Law for the Brown Corpus
Mandelbrot's Law for the Brown Corpus
Mandelbrot’s Law for the Brown Corpus

There are similar laws with corpora. We talked about Zipf’s law (frequency \propto \frac{1}{rank}). There’s also the more complicated (yet more accurate), Mandelbrot’s law: frequency = \frac{P}{(rank + p)^{B}}, where P, B, and p are all parameters of the text. We talked about some potential reasons behind these laws, before I showed that these laws are also true of randomly generated text.

One of the consequences of Zipf’s law is that most words you see only occur a couple of times. Words that only occur once are called hapax legomena. For example, in the Brown corpus, 46% of our bins were hapaxes, yet only 2.2% of the words were hapaxes. Practically, this means that if we ever are making a dictionary, we can eliminate almost half of it while only losing a small amount of content.

We also briefly talked about some other Zipf’s laws, such as:  meaning \propto \sqrt{frequency} and  meaning \propto \frac{1}{\sqrt{rank}}

How to overcome sexual dysfunction

What is sexual dysfunction pdf

The prevalence of antipsychotic-induced sexual and reproductive perform facet-results is high. Clinicians ought to concentrate on them, as a result of they are often badly tolerated, are associated with a low satisfaction and may subsequently lead to low adherence with remedy.

Psychological components could range from by no means having realized how to have an orgasm, to unrealistic expectations from a partner, to feelings of guilt at experiencing pleasure. Orgasmic dysfunction is identified only when a lady has no problem with arousal, solely with climax. The stage of sexual activity at which a girl is having issues may provide some clues.

Orgasmic disorder implies that a woman might take pleasure in sexual exercise however has difficulty reaching orgasm or takes a really very long time to succeed in orgasm. Physical causes are rare, besides in cases of nerve harm within the spine.

Which drugs cause sexual dysfunction

  • Although women can remain sexually active and experience orgasms throughout their lives, sexual activity usually LPMedical – Acheter du Kamagra decreases after age 60.
  • Most typically, any of those responses have psychological problems.
  • Sexual dysfunction refers to a problem(s)that forestalls the person or couple from experiencing satisfaction from sexual activity.
  • Learn what is going on on, the way it can have an effect on intercourse drive and relationships.

Female sexual dysfunction happens when a girl isn’t capable of fully, healthily, and pleasurably experience some or all of the varied bodily levels the physique normally experiences during sexual activity. These phases may be broadly thought of as the need part, the arousal part, and the orgasm part. 137 female inpatients with MS analysis were interviewed, accomplished The Female Sexual Function Questionnaire SFQ28 and underwent neurological assessment. Only 2.2 % of patients had ever mentioned their sexual concerns with a physician. SD were less likely in ladies who assessed their relationship positively however extra frequent in older sufferers and those who had a positive historical past of melancholy.

This implies for the clinician to overtly focus on with the patient of his sexuality and the potential negative impression of antipsychotic remedy on it. The recognition of those problems allows the looking together for a solution. The described cases indicate that fixing the problem is commonly attainable, provided that particular person preferences and subjective influence are taken in account.

Anxiety can do that, for instance, by stopping or slowing the state of sexual pleasure that enables for the lubrication or moistening of the feminine genitalia – an essential step towards fulfilling types of sexual activity. This work aimed to gauge the prevalence and traits of sexual dysfunction in Moroccan patients consulting for a first depressive episode.

The sexual response cycle historically consists of excitement, plateau, orgasm, and determination. Desire and arousal are both a part of the joy phase of the sexual response. To each deal with and forestall sexual dysfunction, ladies ought to perceive how their intercourse organs work and how they’ll reply. The vagina is sort of a muscle, and with inactivity, it becomes more durable to make use of.

Computational Phonology (Guest Speaker Ewan Dunbar, 2/5/13)

Ewan Dunbar, a grad student at UMD, spoke to us about fundamental computational properties of our phonology processors. He focused on the way stress patterns work across different languages, and related them to function machines and the Chomsky hierarchy.

Background Reading
He asked that we read Sentence and Word Complexity and Computational Phonology Part I. He also suggested reading Computational Phonology Part II and Phonological Rules too. We have a summary sheet of all the readings in the Google Drive Resources collection.

Ewan first showed us different stress patterns in various languages and how they were all variations on alternating stress (more detail available here, here, and here). He then showed us a couple Finite State Machines (FSMs), and showed that stress patterns could be identified with FSMs, before generalizing this to all phonological patterns. But FSMs are very limited (see Chomsky Hierarchy lecture) – for example, they can’t recognize the set of palindromes (prove via the pumping lemma). Syntactic structure is an example of pattern class that can’t be recognized by FSMs. This leads us to believe that syntax and phonology are two separate cognitive systems, because of their computationally different complexities.