نتایج جستجو برای: audio signal processing

تعداد نتایج: 866730  

2003
W Li X Y Xue

In this paper, a novel localized robust audio watermarking scheme is proposed. The basic idea is to embed watermark in selected high energy regions, that is, in regions of interest (ROI). By virtue of localization and ROI, the embedded watermark is expected to escape the damages caused by audio signal processing, random cropping and time scale modification etc, because these high energy local r...

2009
Thushara D. Abhayapala Yan Jennifer Wu

Reproduction of a spatial soundfield in an extended region of open space with a designated quiet zone is a challenging problem in audio signal processing. We show how to reproduce a given spatial soundfield without altering a nearby quiet zone. In this paper, we design a spatial band stop filter over the zone of quiet to suppress the interference from the nearby desired soundfield. This is achi...

2004
Rainer Huber Volker Mellert

A new method for the objective assessment and prediction of the perceived audio quality is introduced. It represents an expansion of the speech quality measure qC , introduced by Hansen and Kollmeier (2000). It is based on a psychoacoustically validated, quantitative model of the ”effective” peripheral auditory processing by Dau et al. (1996a, 1997a). To evaluate the audio quality of a given di...

2006
Tsang-Long Pao Wen-Yuan Liao

For past several decades, visual speech signal processing has been an attractive research topic for overcoming certain audio-only recognition problems. In recent years, there have been many automatic speech-reading systems proposed that combine audio and visual speech features. For all such systems, the objective of these audio-visual speech recognizers is to improve recognition accuracy, parti...

2005
Stuart Bray George Tzanetakis

One of the important challenges facing music information retrieval (MIR) of audio signals is scaling analysis algorithms to large collections. Typically, analysis of audio signals utilizes sophisticated signal processing and machine learning techniques that require significant computational resources. Therefore, audio MIR is an area were computational resources are a significant bottleneck. For...

Journal: :Signal Processing Systems 2014
Shigeru Katagiri Atsushi Nakamura Tülay Adali Jianhua Tao Jan Larsen Tieniu Tan

Signal processing including analysis, understanding, detection, estimation, and modelling of the events and trends, the way they evolve, and the abnormalities and anomalies affecting them have attracted many researchers around the globe. Signal processing theory originates from mathematical foundation with astonishing applications which help information technologists discover and invent new rea...

2005
ROBERT C. MAHER

Forensic audio recordings may contain undesired noise that can impair source identification, speech recognition, and other audio processing requirements. In this paper several custom analysis/synthesis algorithms are presented based on a time-varying spectral representation of the noisy signal. The enhancement process adapts to the instantaneous signal behavior and alters the noisy signal so th...

Journal: :CoRR 2010
Kruti Dangarwala Jigar Shah

Just about all the newest living room audio-video electronics and PC multimedia products being designed today will incorporate some form of compressed digitized-audio processing capability. Audio compression reduces the bit rate required to represent an analog audio signal while maintaining the perceived audio quality. Discarding inaudible data reduces the storage, transmission and compute requ...

2009
Alexander Bekiarski Snejana Pleshkova

A moving robot audio system contains a simple microphone or more precise microphone array as an audio sensor. One of the main functions of audio system in the mobile robots is to help them in speaker localization. There are many possibilities to choose the methods for processing of audio information from the corresponding audio robot sensors. The goal in this article is to propose and test the ...

Journal: :CoRR 2016
Shuhui Qu Juncheng Li Wei Dai Samarjit Das

One key step in audio signal processing is to transform the raw signal into representations that are efficient for encoding the original information. Traditionally, people transform the audio into spectral representations, as a function of frequency, amplitude and phase transformation. In this work, we take a purely data-driven approach to understand the temporal dynamics of audio at the raw si...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید