Syllabification by Phone Categorization
This addresses syllabification for speech synthesis and recognition, but it is incremental as it builds on existing methods like hidden Markov models.
The paper tackled the problem of syllabification for speech applications by developing a hybrid genetic algorithm to categorize phones, achieving promising preliminary results on English words.
Syllables play an important role in speech synthesis, speech recognition, and spoken document retrieval. A novel, low cost, and language agnostic approach to dividing words into their corresponding syllables is presented. A hybrid genetic algorithm constructs a categorization of phones optimized for syllabification. This categorization is used on top of a hidden Markov model sequence classifier to find syllable boundaries. The technique shows promising preliminary results when trained and tested on English words.