Visualisation, analysis and quality control of conversational data.
             Rapid and visual insights into the nature, timing and quality of
             time-aligned annotations in conversational corpora.
             For more details, see 
             Dingemanse et al., (2022) <doi:10.18653/v1/2022.acl-long.385>.

An R 'shiny' app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. 
             It is a versatile, general-purpose tool for analyzing textual data. 
             'tall' features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis.

Includes marginal maximum likelihood estimation and joint maximum
    likelihood estimation for unidimensional and multidimensional 
    item response models. The package functionality covers the 
    Rasch model, 2PL model, 3PL model, generalized partial credit model, 
    multi-faceted Rasch model, nominal item response model, 
    structured latent class model, mixture distribution IRT models, 
    and located latent class models. Latent regression models and 
    plausible value imputation are also supported. For details see
    Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>,
    Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>,
    Formann, 1982 <doi:10.1002/bimj.4710240209>,
    Formann, 1992 <doi:10.1080/01621459.1992.10475229>.

Implements the Transcendental Algorithm for Mixtures
    of Distributions (TAMD), a penalized likelihood framework for
    fitting finite Gaussian mixture models. TAMD augments the
    Expectation-Maximization (EM) algorithm with analytic barrier
    terms built from the Hellinger affinity that diverge on the
    singular locus, actively preventing component coalescence and
    weight degeneracy. Provides the core TAMD fitting function,
    closed-form Hellinger affinity and gradient computations, the
    Transcendental Affinity Criterion (TAC) for geometry-aware
    model selection, the regularity index rho (a scalar diagnostic
    for mixture fit quality), and reproduction scripts for all
    simulation studies. Methods are described in Fokoue (2024)
    <doi:10.48550/arXiv.2602.03889>.
    See also Titterington, Smith and Makov (1985,
    ISBN:0-471-90510-4) and Watanabe (2009,
    ISBN:978-0-521-86408-7).