NETtalk
Modello implementato negli anni '80 dalla ricerca di Terrence Sejnowski and Charles Rosenberg e uno dei primi esempi di applicazione delle reti neurali e di applicazione delle teorie del connettivismo .
Questo modello, partendo da un dataset etichettato che associa circa 20000 parole inglesi alla loro trascrizione fonetica, dimostrò di essere in grado di generalizzare a parole sconosciute. Dal paper:
English pronunciation has been extensively studied by linguists and much is known about the correspondences between letters and the ele- mentary speech sounds of English, called phonemes 183). English is a par- ticularly difficult language to master because of its irregular spelling. For example, the "a" in almost all words ending in "ave", such as "brave" and "gave", is a long vowel, but not in "have", and there are some words such as "read" that can vary in pronunciation with their grammatical role. The problem of reconciling rules and exceptions in converting text to speech shares some characteristics with difficult problems in artificial intelligence that have traditionally been approached with rule-based knowledge repre- sentations, such as natural language translation
Architettura
Da wikipedia:
- input: vettore da one-hot da 29 categorie
- layer nascosto: 80 unità
- layer di output: 26 unità
Esempi di input
action @kS-xn 1<>0<< 0 activate @ktxvet- 1<>0>2<< 0 active @ktIv- 1<>0<< 0 activity @ktIvxti 0<>1<0<0 0
Links
Paper Originale: Parallel Networks that Learn to Pronounce English Text