Voiced/unvoiced/silence Classification of Speech Using 2-Stage Neural Networks with Delayed Decision Input

R. Ahn, W. Holmes
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引用次数: 5

Abstract

TWO STAGE NEURAL NETWORK CLASSIFIER This paper proposes a two stage feed-forward neural network classifier capable of determining voiced, unvoiced and silence in the first stage and refining unvoiced and silence decisions in the second stage. Delayed decision from the previous frame's classification along with preliminary decision by the first stage network, zero-crossing ratio and energy ratio enables the second stage to correct the mistakes made by the first stage in classifying unvoiced and silence frames. Comparisons with a single stage classifier demonstrates the necessity of two stage classification techniques. It also shows that the proposed classifier performs excellently.
基于延迟决策输入的两阶段神经网络的语音分类
本文提出了一种两阶段前馈神经网络分类器,该分类器能够在第一阶段确定浊音、浊音和浊音,在第二阶段细化浊音和浊音的判断。前一帧分类的延迟决定和第一阶段网络、过零比和能量比的初步决定,使第二阶段能够纠正第一阶段在对静音帧和静音帧进行分类时所犯的错误。与单阶段分类器的比较表明了两阶段分类技术的必要性。实验还表明,该分类器具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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