I know it becomes harder to find the start and end of phonemes due to co-articulation. I want to know about other problems that co-articulation causes in speech recognition.
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Multiply-articulated sounds like labiovelars or aspirated stops may well be heard as different sounds. They are also subject to great individual variation because of the independent articulations, which must be timed precisely and usually aren't -- voice onset time is never exactly at the beginning of a voiced segment, nor is lip-rounding always timed exactly at the beginning of a labiovelar. So we say, and hear, different things all the time. All we have to depend on is our habits, and our impression of others' habits.– jlawlerJan 12, 2019 at 18:23
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Modern data-driven approaches to speech recognition are ignorant about but robust to this one of many aspects of orthography that are not fully phonetic but occur relatively consistently in the training data.
For one, it is more an issue of mapping n:1 (different realisations of one set of characters), whereas challenges for speech recognition generally revolve around:
1:n (ambiguity):
homophones like
doevsdough,seevssea,wreck a nice beachvsrecognise speechmeta language like
contact at priceline.comvs[email protected],anneal-vsAnil Dash,He told me quote unquote I will kill youvsHe told me "I will kill you.", acronyms
shift vis-a-vis the training data:
out-of-domain and domain-specific words
variations in accents and dialects
a foreign language or mixed language
background noise
the fact that users don't really want a literal transcription:
I'ma, um, I'ma call you on, um, SaturdayvsI'm going to call you on Saturday
answered Jan 12, 2019 at 18:44
