Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method for syllabic stress annotation which does not require manual labels for the learning process, but uses stress labels automatically generated from a multiscale model of rhythm perception. The model outputs a sequence of events, corresponding to the sequences of strong-ak syllables present in speech, based on which a stressed/unstressed decision is taken.  tested our approach on two languages, Catalan and Spanish, and  found that a classifier employing the automatic labels for learning improves performance over the baseline for both languages.  also compared the results of this system with those of an identical learning algorithm, but which employs manual labels for stress, as ll as to the results of a clustering algorithm using the same features. It shod that the system employing automatic labels has a performance close to the one using manual labels, with both classifiers outperforming the clustering algorithm.
['Bogdan Ludusan', 'Antonio Origlia', 'Emmanuel Dupoux']
I am writing a research paper on a idea Rhythm-Based Syllabic Stress Learning Without Labelled Data
[{"from": "human", "value": "I am writing a research paper on a idea Rhythm-Based Syllabic Stress Learning Without Labelled Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  propose a method for syllabic stress annotation which does not require manual labels for the learning process, but uses stress labels automatically generated from a multiscale model of rhythm perception. The model outputs a sequence of events, corresponding to the sequences of strong-ak syllables present in speech, based on which a stressed/unstressed decision is taken.  tested our approach on two languages, Catalan and Spanish, and  found that a classifier employing the automatic labels for learning improves performance over the baseline for both languages.  also compared the results of this system with those of an identical learning algorithm, but which employs manual labels for stress, as ll as to the results of a clustering algorithm using the same features. It shod that the system employing automatic labels has a performance close to the one using manual labels, with both classifiers outperforming the clustering algorithm."}]