Speaker Recognition Problem uses what Deep Learning Algorithms
Speaker Recognition Problem uses what Deep Learning Algorithms
Automatic Speaker Recognition uses what Deep Learning Algorithms is a short video to discuss the Deep Learning Algorithms used for Automatic Speaker Recognition. This can be used for Machine Learning, Deep Learning, or neural network interview question. Speaker Recognition is the process of identifying a speaker by analyzing the spectral shape of the voice signal. This is done by extracting &…
by Zaw Win Aung" A Robust Speaker Identification System"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5 , August 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18274.pdf
Direct URL: http://www.ijtsrd.com/other-scientific-research-area/other/18274/a-robust-speaker-identification-system/zaw-win-aung
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This paper is aimed to implement a robust speaker identification system. It is a software architecture which identifies the current talker out of a set of speakers. The system is emphasized on text-dependent speaker identification system. It contains three main modules: endpoint detection, feature extraction and feature matching. The additional module, endpoint detection, removes unwanted signal and background noise from the input speech signal before subsequent processing. In the proposed system, Short-Term Energy analysis is used for endpoint detection. Mel-frequency Cepstrum Coefficients (MFCC) is applied for feature extraction to extract a small amount of data from the voice signal that can later be used to represent each speaker. For feature matching, Vector Quantization (VQ) approach using Linde, Buzo and Gray (LBG) clustering algorithm is proposed because it can reduce the amount of data and complexity. The experimental study shows that the proposed system is more robust than using the original system and it is faster in computation than the existing one. To implement this system MATLAB is used for programming.
Automatic Attendance System Using Speaker Recognition
by Dr. Zaw Win Aung "Automatic Attendance System Using Speaker Recognition"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18763.pdf
Direct Link: http://www.ijtsrd.com/other-scientific-research-area/other/18763/automatic-attendance-system-using-speaker-recognition/dr-zaw-win-aung
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The main aim of this paper is to develop automatic attendance system using speaker recognition technique. The proposed system is software architecture which allows the user to access the system by making an utterance from microphone and the attendance of corresponding user is marked in the Microsoft Office Excel. The proposed system automates the whole process of taking attendance. The system uses text dependent open-set speaker identification with MFCC features and vector quantization based speaker modeling for authenticating the user. A simple Euclidean distance scoring is used as the classifier. For decision making, the new approach, mean value threshold is proposed to optimize the system performance. The database consists of 60 speech samples which were collected from 20 speakers consisting of 10 male speakers and 10 female speakers. The experimental study shows that the proposed system with mean value threshold achieves better results in recognition accuracy and verification performance than the system with other threshold setting.
