  Reservoir computing is a recurrent machine learning framework that expands
the dimensionality of a problem by mapping an input signal into a
higher-dimension reservoir space that can capture and predict features of
complex, non-linear temporal dynamics. Here, we report on a bulk optical
demonstration of an analog reservoir computer using speckles generated by
propagating a laser beam modulated with a spatial light modulator through a
multimode waveguide. We demonstrate that the hardware can successfully perform
a multivariate audio classification task performed using the Japanese vowel
speakers public data set. We perform full wave optical calculations of this
architecture implemented in a chip-scale platform using an SiO2 waveguide and
demonstrate that it performs as well as a fully numerical implementation of
reservoir computing. As all the optical components used in the experiment can
be fabricated using a commercial photonic integrated circuit foundry, our
result demonstrates a framework for building a scalable, chip-scale, reservoir
computer capable of performing optical signal processing.
