This paper proposes a content-based audio information retrieval and indexing technique based on wavelet transform. The presented approach uses multiresolution decomposition property of the discrete wavelet transform to analyze audio data. The wavelet decomposition of an audio signal highly resembles to its decomposition in sound octaves. A hierarchical indexing scheme is constructed using stati...

This paper presents a new estimator for the velocity of a mobile station in micro-cellular systems. The proposed estimator is based on the zero-crossing rate of the instantaneous frequency of the received signal. The effects of additive noise, scattering distribution, and shadowing on the proposed velocity estimator are analyzed. The IF-based velocity estimator outperforms the conventional esti...

growth of information and communication technologies has influenced the research trends n speech technologies. This research explains a basic speech segmentation application for Arabic language with the aim to further develop a language tutor. The focus is on rabic as there are standards available which help in obtaining better accuracy. The roblem has been formulated in the form of a number of...

This paper presents a voice activity detection (VAD) scheme that is robust against noise, based on an optimally weighted combination of features. The scheme uses a weighted combination of four conventional VAD features: amplitude level, zero crossing rate, spectral information, and Gaussian mixture model likelihood. This combination in effect selects the optimal method depending on the noise co...

1 The author gratefully acknowledges the support of K. C. Wong Education Foundation, Hong Kong. ABSTRACT In this paper, a novel waveform coding approach based on half-wave vector quantization is presented. The input speech signal is divided into frames, each of which is classified as silence, unvoiced and voiced. The voiced category is subdivided into 64 sub-categories according to the length o...

While current approaches for audiovisual data segmentation and classification are mostly focused on visual cues, audio signals may actually play a more important role in content parsing for many applications. An approach to automatic segmentation and classification of audiovisual data based on audio content analysis is proposed. The audio signal from movies or TV programs is segmented and class...

The root mean square (RMS) value of a vibration signal is an important indicator used to represent the amplitude of vibrations in evaluating the quality of highspeed spindles. However, RMS is unable to detect a number of common fault characteristics that occur prior to bearing failure. Extending the operational life and quality of spindles requires reliable fault diagnosis techniques for the an...

For noise-robust automatic speech recognition (ASR), we propose a novel voice activity detection (VAD) method based on a combination of multiple features. The scheme uses a weighted combination of four conventional VAD features: amplitude level, zero crossing rate, spectral information, and Gaussian mixture model (GMM) likelihood. The weights for combination are adaptively updated using minimum...

We investigate four different privacy-sensitive features, namely energy, zero crossing rate, spectral flatness, and kurtosis, for speech detection in multiparty conversations. We liken this scenario to a meeting room and define our datasets and annotations accordingly. The temporal context of these features is modeled. With no temporal context, energy is the best performing single feature. But ...

This paper presents a way for the automatic identification of different voice qualities present in a speech signal which is very beneficiary for detecting any kind of speech by an efficient speech recognition system. Proposed technique is based on three important characteristics of speech signal namely Zero Crossing Rate, Short Time Energy and Fundamental Frequency. The performance of the propo...