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Separating the influences of prereading skills on early word and nonword reading

Separating the influences of prereading skills on early word and nonword reading

Children also performed poorly on all phonological awareness tasks, but despite low scores these measures were well correlated with later reading (correlations were of a similar size to previous stud- ies, e.g., Muter et al., 2004). This is in line with previous findings that phonological awareness tasks are very challenging for prereaders but are still predictive of later reading. As in Carroll and colleagues (2003), children scored slightly better on our rhyme measures, probably because these tasks tapped into sensitivity rather than explicit awareness and involved larger units. Nevertheless, our measure that elicited the lowest scores (phoneme isolation) showed the highest correlations with print mea- sures at baseline and with reading outcomes. This association suggests that explicit awareness of the sounds in words and knowledge of print develop reciprocally. It is possible that orthographic knowledge was particularly helpful for the phoneme isolation task. If a child were able to imagine the printed word, this would provide an additional route for retrieving the sound of the first letter. Auditory skills were also highly correlated with print knowledge and phonological STM and were moderately correlated with phoneme and rhyme awareness, perhaps because they also tapped into children’s ability to judge and/or reproduce the order of sounds (Banai et al., 2009; Talcott et al., 2002; Tallal et al., 1993). Although our auditory measures were highly associated with reading, they did not make a direct contribution after other skills were factored out.

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Hafez: an Interactive Poetry Generation System

Hafez: an Interactive Poetry Generation System

This work is based on our previous poetry gen- eration system called Hafez (Ghazvininejad et al., 2016), which generates poems in three steps: (1) search for related rhyme words given user- supplied topic, (2) create a finite-state acceptor (FSA) that incorporates the rhyme words and con- trols meter, and (3) use a recurrent neural network (RNN) to generate the poem string, guided by the FSA. We address the above-mentioned challenges with the following approaches:

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Finite State Technology in a Verse Making Tool

Finite State Technology in a Verse Making Tool

Once the main tools of the BAD have been devel- oped, we intend to focus on two different lines of development. The first one is to extend to flexibil- ity of rhyme checking. There are as of yet patterns which are acceptable as rhymes to bertsolaris that the system does not yet recognize. For example, the words filma and errima will not be accepted by the current system, as the two rhymes ilma and ima are deemed to be incompatible. In reality, these two words are acceptable as rhymes by bertsolaris, as the l is not very phonetically prominent. However, adding flexibility also involves controlling for over- generation in rhymes. Other reduction patterns not currently covered by the system include phenomena such as synaloepha—omission of vowels at word boundaries when one word ends and the next one begins with a vowel.

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Supervised Rhyme Detection with Siamese Recurrent Networks

Supervised Rhyme Detection with Siamese Recurrent Networks

Previous research on the detection of rhyme is scarce. Reddy and Knight (2011) employed Expectation Maximization (EM) to predict (generate) the most probable scheme (e.g. ’abba’) of a stanza. We use a supervised approach to rhyme detection to model the properties of rhyme itself. An accurate similarity measure between words would benefit an EM. Siamese Recurrent Networks are adept for rhyme, as they learn a (non-linear) similarity metric on variable length character sequences. This metric can be used to gauge the degree of imperfection in a rhyme, and by threshold, for a binary classification. We describe our architecture in section 3.2, followed by experiments and a qualitative error analysis to find the best detection system across languages (German, English, French) and domains (poetry, Hip-Hop).

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Generating Topical Poetry

Generating Topical Poetry

We first hash all related words/phrases into rhyme classes. Each collision generates a candidate rhyme pair (s1, s2), which we score with the maximum of cosine(s1, topic) and cosine(s2, topic). So that we can generate many different sonnets on the same topic, we choose rhyme pairs randomly with prob- ability proportional to their score. After choosing a pair (s1, s2), we remove it, along with any other can- didate pair that contains s1 or s2. Because a poem’s beginning and ending are more important, we assign the first rhyme pair to the last two lines of the sonnet,

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“Poetic” Statistical Machine Translation: Rhyme and Meter

“Poetic” Statistical Machine Translation: Rhyme and Meter

Computing this set exactly involves a standard dy- namic programming sweep over the phrase lattice, including only uncovered source spans. If the maxi- mum source phrase size is k, source sentence length is n and maximum target/source length ratio for a phrase is l (and therefore target sentence is limited to at most ln words), this sweep requires going over O(n 2 ) source ranges, each of which can be produced in k ways, and tracking ln potential lengths in each, resulting in O(n 3 kl) algorithm. This is unaccept- ably slow to be done for each hypothesis (even not- ing that hypotheses with the same set of already cov- ered source position can share this computation).

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Unsupervised Discovery of Rhyme Schemes

Unsupervised Discovery of Rhyme Schemes

is strongly correlated 4 with the predictability of rhyming words. For writing systems where the written form of a word approximates its pronunci- ation, we have some additional information about rhyming: for example, English words ending with similar characters are most probably rhymes. We do not want to assume too much in the interest of language-independence – following from our earlier point in §1 about the nebulous definition of rhyme – but it is safe to say that rhyming words involve some orthographic similarity (though this does not hold for writing systems like Chinese). We therefore initialize θ at the start of EM with a simple similarity measure: (Eq. 5). The addition of = 0.001 ensures that words with no letters in common, like new and you, are not eliminated as rhymes.

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Deep speare: A joint neural model of poetic language, meter and rhyme

Deep speare: A joint neural model of poetic language, meter and rhyme

We focus on quatrain generation in this work, and so the aim is to generate 4 lines of poetry. During generation we feed the hidden state from the pre- vious time step to the language model’s decoder to compute the vocabulary distribution for the cur- rent time step. Words are sampled using a tem- perature between 0.6 and 0.8, and they are resam- pled if the following set of words is generated: (1) UNK token; (2) non-stopwords that were gener- ated before; 16 (3) any generated words with a fre- quency > 2; (4) the preceding 3 words; and (5) a number of symbols including parentheses, single and double quotes. 17 The first sonnet line is gen- erated without using any preceding context.

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On the Romanian Rhyme Detection

On the Romanian Rhyme Detection

Once we detected which words of the dataset rhyme with other words, we could implement the other features stated above. Our tool provides rhyming words for a given input, relevant in automatic or assisted poetry translation. Below are selected words that rhyme with the monosyllabic word “strict”, whose rhyme is “íct”. The output words are syllabified and their stressed vowels are marked. It can be easily observed that all retrieved words have the same rhyme as the input word.

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‘Chosen Comrades’: Yeats’s Romantic Rhymes

‘Chosen Comrades’: Yeats’s Romantic Rhymes

century houses, and the repetitive rhyme of ‘ words ’ with ‘ words ’ brings the poem momentarily in step with polite meaninglessness. The dulled rhymes reflect the difficulty of articulating a poetic response to the events; repetition serves to underline the numb shock while half-rhyme deliberately undermines implicit certainties. Unlike in ‘Under Ben Bulben’, the reader must wait for the rhymed partner rather than have it swiftly follow, suggesting the difficult line between fact and interpretation that the poem must tread. The poem’s rhymes help to keep its uncertainties in play right through to its closing paragraph:

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Effect of Visual-Perceptual Exercises Based on Frostig Model on Reading Improvement in Dyslexic Students

Effect of Visual-Perceptual Exercises Based on Frostig Model on Reading Improvement in Dyslexic Students

freedom 11 is greater than the critical value of t and also because their obtained significance level is less than criterion significance level (0.01), therefore, with 99% of certainty, it could be said that the observed difference between pre-test scores and post-test scores is significant. Thus, the research hypothesis concerning the impact of visual-perceptual exercises based on Frostig’s model on reading words, Words chain, rhyme, calling the figure, text comprehension, words comprehension, voices removal, reading unfamiliar words, letters signs and category signs components and null assumption is rejected. It is also needed to mention that the obtained value of t in the text comprehension component is smaller than the critical amount of t and according to the obtained significance level (0.067) which is smaller than the criterion significance level (0.05), it could be concluded that there is no significant difference between pre-test scores and post-test scores of the text comprehension component.

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A Rule based Approach for Karmina Generation

A Rule based Approach for Karmina Generation

The message of Karmina is more free in its mean- ing and structure. Creating all possible schemas is not a feasible option. However, we managed to find messages that follow certain schemas. They have the same structures with the Schema 1 and Schema 2 . Hence, in this work, the message was generated by using these two schemas only. These two schemas bind the hook and the message to have the same structure, i.e. both have the struc- tures of Dahulu X sekarang Y or Sudah X Y pula. They differ in the types and constraints of the X and Y used. We experimented using a list of posi- tive and negative sentiment words to replace X and Y .

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Mental suffering as a struggle with words: language and emotion

Mental suffering as a struggle with words: language and emotion

thinking is the enactment of the peculiar synthetic char- acter of his understanding of human beings as concrete particular individuals who exist through abstract thinking and conceptual language. The concrete, almost sensible, poetics of his writing works with ways of expressing the general and uniform character of language and thinking through concrete particulars. This emphasis on the com- plexity of the concrete and the abstract is also what brings out the problems involved in our imaginative capacities. The seemingly infinite possibilities that are made real by imagination can also make us lose our sense of reality. This reality is first and foremost characterised by being concrete, that is, a process that has grown together (con- crescere) in a way that our imaginative capacities cannot imitate, produce, or mirror. It is, in other words, a reality that transcends the power of imagination; a reality against whose concreteness our imaginative variations fracture. Kierkegaard describes the difference between concrete reality and imagination in terms of suffering: “[C]ould a human being by means of his imagination experience exactly the same as in reality, live through it in the same way as if he lived through it in reality, learn to know him- self as accurately and profoundly as in the experience of reality – then there would be no meaning in life. In that case, Governance would have structured life wrongly, for to what purpose, then, reality if by means of the imagina- tion one could in advance absorb it in a completely real way; to what purpose, then, the seventy years if in the twenty-second year one could have experienced every- thing! But such is not the case either, and therefore in turn the image produced by the imagination is not that of true perfection; it lacks something – the suffering of reality or the reality of suffering”  52 [p. 188].

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Words that make pills easier to swallow: a communication typology to address practical and perceptual barriers to medication intake behavior

Words that make pills easier to swallow: a communication typology to address practical and perceptual barriers to medication intake behavior

A second limitation is that we measured perceived barriers only after the consultation. Therefore, we were not able to measure possible changes over time. This might be an explanation for some findings that were not predicted by the developed typology. For example, checking whether the patient had understood the given information was associated more frequently with necessity barriers. It is possible that although the nurses used this communication technique to decrease those barriers, they might not have been able to remove them successfully. In other words, it is possible that the patients scored relatively high on these barriers after the consultation, but lower than they would have scored before the consultation. Therefore, future research should include premeasurements of perceived barriers regarding medication, which may help to further refine the developed typology.

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Gifted and Talented UCEA English

Gifted and Talented UCEA English

Sonnet: In its earliest usages this can mean just 'a short poem, often on the subject of love.' Now it is almost always used to denote a fourteen line poem in iambic pentameter. There are two main forms of Sonnet: the 'Shakespearean Sonnet' rhymes abab cdcd efef gg. It was the form favoured by Shakespeare, in his Sonnets (1609), although it is first found in the work of Henry Howard, Earl of Surrey. The three quatrains can be linked together in argument in a variety of ways, but often there is a 'volta' or turn in the course of the argument after the second quatrain. The final couplet often provides an opportunity to sum up the argument of the poem with an epigram. Edmund Spenser's Amoretti (1595) introduced a variant form in which the quatrains are connected by rhyme: abab bcbc cdcd ee. The 'Petrarchan Sonnet', which is the earliest appearance of the form, falls into an octet, or eight line unit, and a sestet, or six line unit. The Petrarchan sonnet form rhymes abbaabba cdecde (although the sestet can follow other rhyme-schemes, such as cdcdcd). Often there is a marked shift in the progression of the argument after the octet in the Petrarchan sonnet, which is sometimes vestigially registered in the Shakespearean form by a change of argument or mood at the start of the third quatrain. Sonnets may be free-standing poems, or they may form part of an

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Bhagvad Gita and Gitanjali: Exploring Consciousness in Tagore

Bhagvad Gita and Gitanjali: Exploring Consciousness in Tagore

Consciousness in Nature’s love for life: Tagore consciously tries to overcome his frail existence, which he pejoratively signals - ‘my eyes’ and ‘my ears’, as they are His unblemished instruments through which He visualizes ‘thy creation’ and He listens to ‘thine own eternal harmony’:” What divine drink wouldst thou have, my God/ from this overflowing cup of my life?/ My poet, is it thy delight to see thy creation/ through my eyes and to stand at the portal/ of my ears silently to listen/ to thine own eternal harmony?” (R. Tagore, English Gitanjali Verse 65). On the other hand, there are Tagore’s imaginative expressions about God’s world being His poetic workshop, like the Sun is “the golden harp”, or the Sunlight is “thy voice pour down in/golden streams breaking through the sky.”, bird’s sweet notes are “thy words will take wings in songs/from every one of my birds’ nests,”, and budding of newborn blooms are “thy melodies will break forth in flowers in all my forest groves.” (R. Tagore, English Gitanjali Verse 19).

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Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting

Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting

the works discussed below implement models that generate complete verses from scratch (including verse structure), which is the goal of the models we aim to evaluate. In terms of manual evalua- tion, Barbieri et al. (2012) have a set of annota- tors evaluate generated lyrics along two separate dimensions: grammar and semantic relatedness to song title. The annotators rate the dimensions with scores 1-3. A similar strategy is used by Gerv´as (2000), where the author has annotators evaluate generated verses with regard to syntactic correct- ness and overall aesthetic value, providing scores in the range 1-5. Wu et al. (2013) have anno- tators determine the effectiveness of various sys- tems based on fluency as well as rhyming. Some heuristic-based automated approaches have also been used, e.g., by Oliveira et al. (2014) who use a simple automatic heuristic that awards lines for ending in a termination previously used in the gen- erated stanza. Malmi et al. (2015) evaluate their generated lyrics based on the verses’ rhyme den- sity, on the assumption that a higher rhyme density means better lyrics.

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A Computational Analysis of Style, Affect, and Imagery in Contemporary Poetry

A Computational Analysis of Style, Affect, and Imagery in Contemporary Poetry

more references to psychological states and explore the emotional world with more depth and intensity? We examine this question using several existing sentiment lexicons available for sentiment analy- sis research. One is the Harvard General Inquirer, which consists of 182 word categories, including basic sentiment categories, categories for concrete objects, and categories for abstract concepts (Stone et al., 1966). Another sentiment lexicon is the Linguistic Inquiry and Word Count (LIWC) (Pen- nebaker et al., 2001). While the General Inquirer was designed for content analysis, LIWC was de- signed to facilitate the understanding of individuals’ cognitive and emotional states through text analy- sis. As a result, most of the categories in LIWC in- volve mental activity, with over 4, 500 words related to affective, social, and cognitive processes. Six cat- egories from the Harvard General Inquirer and two categories from LIWC were selected because they are most suitable for our purpose of analyzing el- ements of poetic craft. These features are summa- rized in Table 1.

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Words that describe chronic musculoskeletal pain: implications for assessing pain quality across cultures

Words that describe chronic musculoskeletal pain: implications for assessing pain quality across cultures

There are a number of limitations of this study that should be considered when interpreting the results. 1) To our knowl- edge, this is the first time that patients with chronic pain in Nepal were asked to describe their pain, and their responses were coded by a single investigator (SS) to determine the rates with which different domains were mentioned. It would have been ideal if two independent researchers had translated the participants’ responses in order to be able to evaluate the reliability of the translation. 2) The majority of the study par- ticipants came from the community and were not specifically seeking pain treatment, even though they had to rate their usual pain intensity as at least 4 of 10 on a 0–10 NRS. The findings might have been different if more participants had been recruited from the hospital who were seeking treatment for pain or who might have had more severe pain. Therefore, the current findings should be replicated in additional samples of patients from Nepal to determine their reliability. 3) The sample size, while adequate for obtaining good estimates of the rates that different pain domains are used for those domains that are fairly common, might be considered low for estimating the rates of descriptors that are less commonly used. Thus, subdomains that were mentioned only twice in the sample (2%) might in fact be used more (≥3%) in the population. This is another reason for replicating the current findings in additional samples of patients; ideally, samples that are even larger than the sample size used for this study. 4) We did not compare the findings of this study to data from a sample from the USA collected at the same time as the data collected here. Instead, we compared the words used by individuals with chronic pain in the Nepalese sample with the words used by the participants in the studies that were completed in 2011 and 2013. 9,10 Although it seems unlikely

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Android Smartphone Based Intelligent Wheel Chair for Physical Challenged Patients

Android Smartphone Based Intelligent Wheel Chair for Physical Challenged Patients

Physically Challenged (Paralysis / Accident Cases) where some organs are paralyzed. The patients whoever suffered from this can use a wheelchair for navigation. As they can’t apply full force to control their wheelchair, there will be requirement of simple application for controlling their wheelchair. The user will control the wheelchair from the Android Smartphone as per the requirement. Android Smartphone will have an application, where it will transmit some data to wheelchair for movement.

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