Probabilistic Pronunciation Modeling a Theory 今 Recognizer goal AM K=argmaxk P(KlA)=argmaxk P(Ak)P(K) gs applying independent assumption LM P(Ak=In P(a,kn) ,s Pronunciation modeling part-via introducing surface s P(ak)=∑(ak,s)P(sk) Refined AM S y mboS Output Prob a: Acoustic signal, k: IF s: GIF K, S: corresponding string Center of speech Technology, Tsinghua University Slide 11Center of Speech Technology, Tsinghua University Slide 11 ❑ Theory ❖ Recognizer goal ➢ K* =argmaxK P(K|A) = argmaxK P(A|K) P(K) ❖ Applying independent assumption ➢ P(A|K) = n P(an |kn ) ❖ Pronunciation modeling part – via introducing surface s ➢ P(a|k) = s P(a|k,s) P(s|k) ❖ Symbols ➢ a: Acoustic signal, k: IF, s: GIF ➢ A, K, S: corresponding string AM LM Refined AM Output Prob. Probabilistic Pronunciation Modeling