Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an automatic speaker recognition system for intelligence applications. The system has to provide functionalities for a speaker skimming application in which databases of recorded conversations belonging to an ongoing investigation can be annotated and quickly browsed by an operator. The paper discusses the criticalities introduced by the characteristics of the audio signals under consideration - in particular background noise and channel/coding distortions - as ll as the requirements and functionalities of the system under development. It is shown that the performance of state-of-the-art approaches degrades significantly in presence of moderately high background noise. Finally, a novel speaker recognizer based on phonetic features and an ensemble classifier is presented. Results show that the proposed approach improves performance on clean audio, and suggest that it can be employed towards improved real-world robustness.
['Enrico Marchetto', 'Federico Avanzini', 'Federico Flego']
I am writing a research paper on a idea An automatic speaker recognition system for intelligence applications
[{"from": "human", "value": "I am writing a research paper on a idea An automatic speaker recognition system for intelligence applications"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an automatic speaker recognition system for intelligence applications. The system has to provide functionalities for a speaker skimming application in which databases of recorded conversations belonging to an ongoing investigation can be annotated and quickly browsed by an operator. The paper discusses the criticalities introduced by the characteristics of the audio signals under consideration - in particular background noise and channel/coding distortions - as ll as the requirements and functionalities of the system under development. It is shown that the performance of state-of-the-art approaches degrades significantly in presence of moderately high background noise. Finally, a novel speaker recognizer based on phonetic features and an ensemble classifier is presented. Results show that the proposed approach improves performance on clean audio, and suggest that it can be employed towards improved real-world robustness."}]