Integrating Neural Networks into Computer Speech Recognition Systems
نویسنده
چکیده
( acoustic observations, modeling subphonetic acoustic events e.g., closures, bursts, transitions). Current HMM-based r " speech recognition systems typically model phonetic units, o phones" (e.g., the sound "m" in the word "map"), with a e c sequence of such states. Sequences of phone models can b oncatenated to form word models. Word models can be e n connected according to grammatical constraints forming larg etworks that model any allowable sentence within an applit cation. This approach allows a hierarchy of levels of linguis ic description to be encoded within a uniform mathematical framework.
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