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4 articles for “audio-only speaker identification”
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Audio-Only Speaker Identification using Principal Component Analysis based Back-Propagation Learning Neural Network in Noisy Environment
Abstract: This paper introduces text dependent speaker identification system on Principal Component Analysis based Back-Propagation learning neural network which deals with detecting a particular speaker from a known populations under noisy environment. For audio pre-processing, ends point detection, silence parts removal, frame segmentation and windowing techniques have been used and wiener filter has been applied to remove the background noise from the audio speech utterances. To reduce the dimension of the …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 1–10 Read article
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Speaker Identification using Hopfield Neural Network based Classifier
Abstract: The aim of this work is to enhance the performance of speaker identification using Hopfield neural network algorithm. Speech signals are collected from VALID Audio-Visual dataset and some speech signal pre-processing techniques are applied to process the speech to feed the Hopfield neural network algorithm. Filtering technique is applied to remove the noises from the speech signals. MFCC based standard speech feature extraction technique is used to extract the speech …
Published in Journal Of Network security · Vol. 3, Issue 2, 2015 · pp. 32–35 Read article
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Back-Propagation Neural Network Based Speaker Identification Under Noise Distortion
Abstract: The aim of this paper is to evaluate the performance of the proposed speaker identification system where Wiener filtering technique has been used to eliminate the background white Gaussian noises and linear discriminant analysis has been used to reduce the dimension of the speech features. Since the audio signal captures more environmental noises than other biometrics modalities, the main emphasis of this paper is to analyze the problem domains of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 1–6 Read article
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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article