XMM model decoders for the browser

This library is intended to be used with the original XMM library, or its Node.js wrapper xmm-node, which takes care of turning phrases and training sets into statistical models, besides allowing to do exactly the same things as xmm-client, server-side.

xmm-client contains 4 classes :

  • PhraseMaker, which eases the creation of XMM-compatible phrases (i.e. time series recordings of dimension n, packed with metadata into JS objects), that can then be passed to XMM.
  • SetMaker, which eases the management of training sets, aka collections of Phrases. A SetMaker should only contain phrases with the same configuration (bimodality, dimension, input dimension, column names), only labels and lengths may vary. Training sets can also be passed to XMM directly to generate a corresponding GMM or HHMM model.
  • GmmDecoder, which takes a GMM model generated by XMM and outputs some estimation results when it's fed with an input vector
  • HhmmDecoder, which does the same with a Hierarchical HMM model generated by XMM.

installation :

npm install [--save] Ircam-RnD/xmm-client

documentation :


es6 example :

import { PhraseMaker, HhmmDecoder } from 'xmm-client';
const phraseMaker = new PhraseMaker({
    column_names: ['gyrAlpha', 'gyrBeta', 'gyrGamma'],
    label: 'someGesture'

const hhmmDecoder = new HhmmDecoder();

credits :

This library is developed by the ISMM team at IRCAM, within the context of the RAPID-MIX project, funded by the European Union’s Horizon 2020 research and innovation programme.
Original XMM code authored by Jules Françoise, ported to JavaScript by Joseph Larralde.
See github.com/Ircam-RnD/xmm for detailed XMM credits.