A Temporal Extension of Latent Dirichlet Allocation for Unsupervised Acoustic Unit Discovery. (arXiv:2206.11706v2 [eess.AS] UPDATED)

Latent Dirichlet allocation (LDA) is widely used for unsupervised topic
modelling on sets of documents. No temporal information is used in the model.
However, there is often a relationship between the corresponding topics of
consecutive tokens. In this paper, we present an extension to LDA that uses a
Markov chain to model temporal information. We use this new model for acoustic
unit discovery from speech. As input tokens, the model takes a discretised
encoding of speech from a vector quantised …

arxiv discovery extension temporal unsupervised