>>16
Speech recognition will end up needing AI if it ever wants to get the level of the average human in correct recognition. A lot of words sound almost the same, and the phonemes in many cases get changed drastically due to idiosyncrasy in pronunciation. The brain does not process speech in real time in the sense that it just listens to the phonemes and compares them against the set of all possible phonemes and then matches them to a semantic understanding. No, that would make us catatonic. It uses highlighted conditioning to register the phonemes used in the language, and then combines them with a semantic understanding of the current context, to create a predictive analysis model for parsing speech. If you've ever noticed that when you're not paying attention / expecting a certain word it's very hard to make out what someone says if you lost the beginning of the word, because then the brain has to switch context, in a sense a "missed branch", and has to evaluate the running context and check against many more phoneme / semantic pairs. That's why almost all speech processing models of today that are the most accurate are trained over certain sets of words with certain intonations, and the model has to be trained for new pronunciations, no one model even now works on an unlimited domain in English. If you mention words it doesn't know it won't piece them together from the pronunciation, it'll just try a closest case scenario, since it does not "understand" what is being said, as in, it has no grasp on semantics, where humans know that an unrecognized word is probably a new word, and they're able to reconstruct it using phoneme pairs. Computers cannot recognize new words without an NLP model.