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This paper introduces the kepstrum method of identification of acoustic transfer functions and its realtime application in techniques such as speech enhancement and noise cancellation. By using kepstrum (known elsewhere as complex cepstrum) analysis, we will show that the kepstrum method is reliable and applicable to real-time processing by providing an(More)
This paper introduces a word boundary detection algorithm that works in a variety of noise conditions including what is commonly called the ‘cocktail party’ situation. The algorithm uses the direction of the signal as the main criterion for differentiating between desired-speech and background noise. To determine the signal direction the algorithm(More)
In this paper, we use the novel method of using features extracted from the time-frequency image representation of a sound signal in an audio surveillance application. In particular, we investigate two image representations: linear grayscale and log grayscale. We first divide a sound signal into smaller frames and apply a windowing function. The absolute(More)
Institute of Mathematics of the Academy of Sciences of the Czech Republic provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use. This paper has been digitized, optimized for electronic delivery and stamped with digital signature within the project DML-CZ: The Czech Digital(More)
This paper presents a special nonlinear switched Griffiths-Jim beamformer (SGJBF) structure. The main objective of this paper is to reduce the background noise from an acquired speech signal. The interference we considered here is non-stationary in nature and can arrive from a variety of potential sources; for example, competing talkers, radio, TV and so(More)
A sound signal produces a unique texture which can be visualized using a spectrogram image and analyzed for automatic sound recognition. In this paper, we explore the use of a well-known image texture analysis technique called the gray-level co-occurrence matrix (GLCM) for sound recognition in an audio surveillance application. The GLCM captures the(More)