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result(s) for
"Lyricist"
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Shah Rukh Khan and Sunfeast Dark Fantasy celebrate the power of imagination in its latest campaign
in
Lyricists
2025
Trade Publication Article
The grammatical structure used by a Tamil lyricist: a linear regression model with natural language processing
by
Raja, Saviour Prakash Gnana Prakasam Louis
,
Venkatesan, Ramalingam Viswanathan
in
Analysis of covariance
,
Application of Soft Computing
,
Artificial Intelligence
2023
The study examines the POS tagger's precise usage of words that are used by Tamil lyricists in their poems. Many NLP tasks, including sentiment analysis, machine translation, and voice recognition, consider POS tagging to be a preparatory step. The POS labels for Tamil words have been determined through several investigations. The research does not look at the precision of the POS tagger for unrecognized keywords or words that do not occur in the lexicon. The practice of categorizing each word in a phrase according to its grammatical function is known as POS tagging. Since the NLP software will come across terms that are not in its lexicon in real-world applications, the presence of unfamiliar words is a common problem in POS tagging. Tamil's agglutinative structure makes language challenging for computers to understand. In-depth research on Tamil phrases has highlighted the need for more research on Dravidian languages, as well as the process of annotating syntactic categories aimed at apiece word in the corpus, and Tamil POS tagger is generating an annotated corpus for Tamil lyricist lyrics. The Friedman Two-way Analysis of Variance was employed by the writers to learn more about the lyricist's use of grammar in this context. Linear regression is a data analysis approach that establishes a causal association amid variables by fit a linear model toward the data. The investigation's findings demonstrated how greatly the lyricists' linguistic decisions varied.
Journal Article
Applying Elements of Spoken Prosody to Sung Expression
2025
SYLLABIC STRESS In her textbook Speech and Voice Science, author, professor, and speechlanguage pathologist Alison Behrman highlights the \"basic building blocks of prosody,\" one of which is syllabic stress. According to Behrman's definition, when executing emphasized syllables in speech, we tend to use a higher pitch (f0) than we do with unemphasized syllables.4 We also use greater intensity or loudness, and longer duration on emphasized syllables. Since the first syllable receives the emphasis, speakers are likely to assign that syllable a higher pitch, greater intensity, and slightly longer duration. By placing the unemphasized syllable \"-de\" on the weaker fourth beat of the measure, lesser intensity than the first syllable is similarly implied. [...]Schubert uses explicit pitch contour (by raising the pitch of the emphasized syllable) and implied intensity contour (by placing the emphasized syllable on a strong rhythmic beat in the measure) to assist the vocalist in interpreting von Schober's text: \"Du holde.\" At the end of the opening melodic phrase, Schubert once again uses explicit pitch contour and implied intensity contour on the word \"Stunden\" (Example 1, m. 6). Since both syllables are written on quarter notes, there is no difference in duration.
Journal Article