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Adaptive Threshold Estimation of Open Set voiceprint recognition Based on OTSU and Deep Learning

Journal of Applied Mathematics and Physics 2020年第11期8卷 2671-2682页

作者： Xudong Li Xinjia Yang Linhua Zhou School of Science Changchun University of Science and Technology Changchun China Provincial Demonstration Center for Experimental Mathematics Education (Changchun University of Science and Technology) Changchun China

Aiming at the problem of open set voiceprint recognition, this paper proposes an adaptive threshold algorithm based on OTSU and deep learning. The bottleneck technology of open set voiceprint recognition lies in the calculation of similarity values and thresholds of speakers inside and outside the set. This paper combines deep learning and machine learning methods, and uses a Deep Belief Network stacked with three layers of Restricted Boltzmann Machines to extract deep voice features from basic acoustic features. And by training the Gaussian Mixture Model, this paper calculates the similarity value of the feature, and further determines the threshold of the similarity value of the feature through OTSU. After experimental testing, the algorithm in this paper has a false rejection rate of 3.00% for specific speakers, a false acceptance rate of 0.35% for internal speakers, and a false acceptance rate of 0 for external speakers. This improves the accuracy of traditional methods in open set voiceprint recognition. This proves that the method is feasible and good recognition effect.

关键词： voiceprint recognition Deep Neural Network (DNN) OTSU Adaptive Threshold

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On Identity Authentication Technology of Distance Education System Based on voiceprint recognition

On Identity Authentication Technology of Distance Education ...

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第三十届中国控制会议

作者： LI Bo Electronics & Information Engineering College,Liaoning University of Technology,Jinzhou 121001,P.R.China

＜正＞In order to improve the efficiency of the identity authentication of the distance education system,the existing authentication technology of the system is *** this paper,the voiceprint recognition method based on HMM/ANN hybrid model is presented,and the novel identity authentication interfaces are developed by *** the analysis of the voiceprint recognition technology,the operation principle and the design process of the distance education system are described in *** system simulation and a mass of the experiments,the identity authentication technology of the distance education system based on the voiceprint recognition has higher identity recognition rate with feasibility.

关键词： voiceprint recognition Distance education Model Identity authentication

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Research on blind source separation of operation sounds of metro power transformer through an Adaptive Threshold REPET algorithm

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Railway Sciences 2024年第5期3卷 609-621页

作者： Liang Chen Liyi Xiong Fang Zhao Yanfei Ju An Jin Railway Science and Technology Research and Development Center China Academy of Railway Sciences Corporation LimitedBeijingChina Development and Reform Department China State Railway Group Co.Ltd.BeijingChina

Purpose–The safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro *** voiceprint technology,the sounds emitted by the transformer can be monitored in real-time,thereby achieving real-time monitoring of the transformer’s operational ***,the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer,severely impacting the accuracy and reliability of voiceprint ***,effective preprocessing steps are required to identify and separate the sound signals of transformer operation,which is a prerequisite for subsequent ***/methodology/approach–This paper proposes an Adaptive Threshold Repeating Pattern Extraction Technique(REPET)algorithm to separate and denoise the transformer operation sound *** analyzing the Short-Time Fourier Transform(STFT)amplitude spectrum,the algorithm identifies and utilizes the repeating periodic structures within the signal to automatically adjust the threshold,effectively distinguishing and extracting stable background signals from transient foreground *** REPET algorithm first calculates the autocorrelation matrix of the signal to determine the repeating period,then constructs a repeating segment *** comparison with the amplitude spectrum of the original signal,repeating patterns are extracted and a soft time-frequency mask is ***–After adaptive thresholding processing,the target signal is *** conducted on mixed sounds to separate background sounds from foreground sounds using this algorithm and comparing the results with those obtained using the FastICA algorithm demonstrate that the Adaptive Threshold REPET method achieves good separation ***/value–A REPET method with adaptive threshold is proposed,which adopts the dynamic threshold ad

关键词： Transformer voiceprint recognition Blind source separation Mel frequency cepstral coefficients(MFCC) Adaptive threshold

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A long-duration Speech Semantic recognition and Summarization Model for multi-speaker Conversations

A long-duration Speech Semantic Recognition and Summarizatio...

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第43届中国控制会议

作者： Mingzhen Song Weifeng Liu Chuanzhao Xu Jiating Wang Shaanxi University of Science and Technology China Jikan Research Institute of Engineering Investigations and Design CoLtd

This paper aims to propose a comprehensive solution to address challenges in the field of audio processing for longduration,multi-speaker conversational *** identified issues include multi-speaker voice separation,difficulties in handling long temporal sequences,and the high redundancy in generating speech scene *** proposed solution encompasses four modules:Firstly,addressing the issue of complex background noise interference in speech signals by introducing Deep Extractor for Music Sources with extra Components(Demucs) audio separation and denoising technology to effectively extract and suppress ***,employing a combined approach of Convolutional Neural Network(CNN) and self-attention to extract multi-scale features for speaker identification in a multi-speaker ***,the Conformer model is trained using a large-scale Chinese speech database to tackle challenges in processing extended temporal sequences,ensuring the accurate transformation of speech information into textual ***,the latest Generative Pre-trained Transformer-3.5(GPT-3.5) model undergoes fine-tuning using a Chinese text summarization *** process enables the generation of text summaries,extracting key points from multi-speaker long-duration *** effectiveness of the proposed algorithms is validated through speech scene experiments in various scenarios.

关键词： Speech recognition voiceprint recognition Text Summarization

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