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2011•Journal of Anqing Teachers CollegeRequires access

Speech Signal Processing by Digital Filter Based on MATLAB

Ling Zhou

Open publisher page 2 citations

Abstract

Time-domain waveform and frequency spectrum of the recorded speech signals are analyzed by sampling.The performance indexes of digital filters are given.Two methods of window function and bilinear transformation are used to design the digital filters.The speech signal is filtered by the filters,and then magnitude-frequency responses of the signal before and after filtering are received.The advantages of two digital filters in speech signal processing are demonstrated by comparing different methods for filtering simply and effectively.

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What this paper is about

Time-domain waveform and frequency spectrum of the recorded speech signals are analyzed by sampling.The performance indexes of digital filters are given.Two methods of window function and bilinear transformation are used to design the digital filters.The speech signal is filtered by the filters,and then magnitude-frequency responses of the signal before and after filtering are received.The advantages of two digital filters in speech signal processing are demonstrated by comparing different methods for filtering simply and effectively.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Time-domain waveform and frequency spectrum of the recorded speech signals are analyzed by sampling.The performance indexes of digital filters are given.Two methods of window function and bilinear transformation are used to design the digital filters.The speech signal is filtered by the filters,and then magnitude-frequency responses of the signal before and after filtering are received.The advantages of two digital filters in speech signal processing are demonstrated by comparing different methods for filtering simply and effectively.

Key concepts: Bilinear transform, Computer science, Digital filter, Window function, Speech processing, Speech recognition, SIGNAL (programming language), Signal processing

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