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Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation. [1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
Other options are to link to the corresponding entry in Wiktionary, or to include an audio file together with the transcription. Consider that Wikipedia is not a dictionary when thinking of adding a pronunciation to an article; also, if the pronunciation is included in the main article, it is best not to repeat it in various sub-articles ...
The pronunciation is encoded using a modified form of the ARPABET system, with the addition of stress marks on vowels of levels 0, 1, and 2. A line-initial ;;; token indicates a comment. A derived format, directly suitable for speech recognition engines is also available as part of the distribution; this format collapses stress distinctions ...
Normally, sound files are presented on Wikipedia pages using the Template:Listen or its related templates. However, it is also possible to present an audio file without any template. [[File:Accordion chords-01.ogg]] Caption. The parameter |thumbmay be used to give the file a caption. That will also float the playbutton to the right.
Square brackets are used with phonetic notation, whether broad or narrow [17] – that is, for actual pronunciation, possibly including details of the pronunciation that may not be used for distinguishing words in the language being transcribed, but which the author nonetheless wishes to document. Such phonetic notation is the primary function ...
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.