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Introduction to Speech Processing

This is a collection of pedagogical material within the topic of speech and language technology. The idea is to provide teachers material for their courses, where they can pick and choose material which is appropriate for their own courses and self-study material on-line for anyone interested.

Authors:  Tom BäckströmOkko RäsänenAbraham ZewoudiePablo Pérez ZarazagaLiisa Koivusalo
Updated:  2022-01-27
Source:  https://wiki.aalto.fi/display/ITSP/Introduction+to+Speech+Processing
Keywords:  speechlanguagecommunicationeducationmachine-learningEnglish

open   documented  

Scikit-learn

Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities.

Authors:  Jérémie du BoisberrangerJoris Van den BosscheLoïc EstèveThomas J. FanAlexandre GramfortOlivier GriselYaroslav HalchenkoNicolas HugAdrin JalaliJulien JerphanionGuillaume LemaitreChristian LorentzenJan Hendrik MetzenAndreas MuellerVlad NiculaeJoel NothmanHanmin QinBertrand ThirionTom Dupré la TourGael VaroquauxNelle VaroquauxRoman Yurchak
Updated:  2022-01-18
Source:  https://scikit-learn.org/stable/
Keywords:  machine-learningPythonprogrammingclustering

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MNE-Python

Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data: MEG, EEG, sEEG, ECoG, NIRS, and more.

Authors:  Alexandre GramfortMartin LuessiEric LarsonDenis A. EngemannDaniel StrohmeierChristian BrodbeckRoman GojMainak JasTeon BrooksLauri ParkkonenMatti S. Hämäläinen
Updated:  2021-12-02
Source:  https://mne.tools/stable/index.html
Keywords:  experimentPythondatamachine-learningneuroscience

open   documented  

Nasalization from Acoustic Features (NAF)

R code implementing a methodology for the automatic measurement of vowel nasalization from acoustic data.

Authors:  Christopher Carignan
Updated:  2021-02-04
Source:  https://github.com/ChristopherCarignan/NAF/
Keywords:  nasalizationphoneticsmachine-learningMFCCacousticsR

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Chinese Readability Index Explorer (CRIE)

The Chinese Readability Index Explorer (CRIE) is composed of four subsystems and incorporates 82 multilevel linguistic features. CRIE is able to conduct the major tasks of segmentation, syntactic parsing, and feature extraction.

Authors:  Yao-Ting SungTao-Hsing ChangWei-Chun LinKuan-Sheng HsiehKuo-En Chang
Updated:  2019-02-18
Source:  http://www.chinesereadability.net/CRIE/?LANG=CHT
Keywords:  linguisticssyntaxphoneticsmachine-learningChinese