Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  investigates the problem of how to partition unknown speech utterances into clusters, such that the overall within-cluster homogeneity of speakers' voice characteristics can be maximized. The within-cluster homogeneity is characterized by the likelihood probability that a cluster model, trained using all the utterances within a cluster, matches each of the within-cluster utterances. Such probability is then maximized by using a genetic algorithm, which determines the best cluster where each utterance should be located. For greater computational efficiency, also proposed is an alternative solution that approximates the likelihood probability with a divergence-based model similarity. The method is further designed to estimate the optimal number of clusters automatically.
['Wei-Ho Tsai', 'Hsin-Min Wang']
I am writing a research paper on a idea On Maximizing the Within-Cluster Homogeneity of Speaker Voice Characteristics For Speech Utterance Clustering
[{"from": "human", "value": "I am writing a research paper on a idea On Maximizing the Within-Cluster Homogeneity of Speaker Voice Characteristics For Speech Utterance Clustering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  investigates the problem of how to partition unknown speech utterances into clusters, such that the overall within-cluster homogeneity of speakers' voice characteristics can be maximized. The within-cluster homogeneity is characterized by the likelihood probability that a cluster model, trained using all the utterances within a cluster, matches each of the within-cluster utterances. Such probability is then maximized by using a genetic algorithm, which determines the best cluster where each utterance should be located. For greater computational efficiency, also proposed is an alternative solution that approximates the likelihood probability with a divergence-based model similarity. The method is further designed to estimate the optimal number of clusters automatically."}]