talker-specificity

Speech recognition: Recognizing the familiar, generalizing to the similar, and adapting to the novel

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At long last, we have finished a substantial revision of Dave Kleinschmidt‘s opus “Robust speech perception: Recognize the familiar, generalize to the similar, and adapt to the novel“. It’s still under review, but we’re excited about it and wanted to share what we have right now.

Phonetic recalibration via belief updating
Figure 1: Modeling changes in phonetic classification as belief updating. After repeatedly hearing a VOT that is ambiguous between /b/ and /p/ but occurs in a word where it can only be a /b/, listeners change their classification of that sound, calling it a /b/ much more often. We model this as a belief updating process, where listeners track the underlying distribution of cues associated with the /b/ and /p/ categories (or the generative model), and then use their beliefs about those distributions to guide classification behavior later on.

The paper builds on a large body of research in speech perception and adaptation, as well as distributional learning in other domains to develop a normative framework of how we manage to understand each other despite the infamous lack of invariance. At the core of the proposal stands the (old, but often under-appreciated) idea that variability in the speech signal is often structured (i.e., conditioned on other variables in the world) and that an ideal observer should take advantage of that structure. This makes speech perception a problem of inference under uncertainty at multiple different levels Read the rest of this entry »