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International Symposium on Communications and Information Technologies (ISCIT)

作者： Cherdchai Eamdeelerd Kraisin Songwatana Department of Telecommunication Engineering Faculty of Engineering King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand

This paper presents the audio noise classification using Bark scale features and K-NN technique. This paper uses audio noise signal from NOISEX-92 (12 types). We determine the transfer functions from linear predictive coding (LPC) coefficient of noise signal on Bark scale and use K-NN technique to classify them. The results will be used for optimization of speech recognition model in the presence of noise. The highest average accuracy for audio noise classification is obtained when K=3 and median over 5 consecutive frames.

关键词： Working environment noise Speech recognition Feature extraction Speech analysis Speech enhancement linear predictive coding Background noise Signal analysis Electronic mail Transfer functions

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Comparisons of maximum system lifetime in diverse scenarios for body sensor networks

Comparisons of maximum system lifetime in diverse scenarios ...

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International Conference on Computer and Information Technology (ICCIT)

作者： Nazrul Islam Mondal Shahid Uz Zaman Abdullah Al Masud Jahangir Alam Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Bangladesh Department of Electronic and Telecommunication International Islamic University Chittagong Bangladesh Department of Computer Science & Engineering Rajshahi University of Engineering and Technology Bangladesh Department of Electronic and Telecommunication International Islamic University Chittagong Bangladesh

In this paper, the main target is to compare the system lifetimes in diverse scenarios based on our new energy dissipation model in the body sensor network as well as maximize the system lifetime of sensor nodes when they will make communication among body sensors and personal communication unit. Nowadays, the ultra low energy consumption is the very much important challenge for medical applications. The best compression technique like LPC is selected for energy saving based on some calculations. This research work studies and analyzes the transceiver energy consumption for different compression algorithms and select the best technique like LPC for energy saving. Formulation of a linear programming problem is also the important part of this research work, where is to maximize the system lifetime which is equivalent to the time until the first node runs out of battery. Maximum system lifetimes are calculated by MATLAB optimization technique using and without using efficient compression algorithm like LPC in various environments. Results show that maximum system lifetimes calculated in different scenarios using efficient compression technique like LPC is better than without using compression technique.

关键词： Body sensor networks linear predictive coding Sensor systems Energy consumption Compression algorithms Energy dissipation Mathematical model Medical services Biomedical equipment Algorithm design and analysis

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Incorporating Formant Cues into Distributed Speech Recognition Systems

Incorporating Formant Cues into Distributed Speech Recogniti...

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3rd International Symposium on Communications, Control, and Signal Processing (ISCCSP 2008), vol.3

作者： Atta Norouzian Sid-Ahmed Selouani Hesham Tolba Douglas O'Shaughnessy INRS-EMT University of Quebec Montreal QUE Canada INRS-EMT University of Quebec Montreal Quebec Campus Shippigan University of Moncton Shippigan New Brunswick Canada INRS-EMT University of Quebec Montreal

The current front-end for distributed speech recognition (DSR) systems provided by European Telecommunications Standards Institute (ETSI) is mainly based on the state-of-the-art MFCC features. The method proposed in this paper aims to improve the performance of the present ETSI DSR-XAFE (XAFE: extended Audio Front-End). For this purpose two sets of acoustical features namely formant-like features and MFCC features are integrated under the multi-stream framework to form a feature vector which is more robust against additive noise. It is shown that for noisy speech, combining cepstral coefficients with main spectral peaks also known as formant-like features, using the multi-stream framework, leads to significant improvement in word recognition accuracy relative to word accuracy obtained for MFCCs alone.

关键词： Speech recognition Automatic speech recognition Mel frequency cepstral coefficient Data mining Telecommunication standards Noise robustness linear predictive coding Additive noise Cepstral analysis Cepstrum

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Digital audio watermarking algorithm based on linear predictive coding in wavelet domain

Digital audio watermarking algorithm based on linear predict...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Wang Rangding Xu Dawen Chen Jiner Du Chengtou CKC Software Laboratory Ningbo University Ningbo Zhejiang China

A digital audio watermarking algorithm based on discrete wavelet transform is presented. A visually significant binary image via some pre-processing and SS modulating is embedded in audio low-middle frequency coefficients in wavelet domain. A scheme of watermark detection is presented by using linear predictive coding, and it does not use the original signal during extracting watermark. The BER is improved 10%-15% in this algorithm compared with the algorithm in Wang R.D. and Chai P.Q. (2003). Experimental results show that the watermark is imperceptible and the algorithm is robust to many attacks, such as low pass filtering, resampling, MP3 compression and so on.

关键词： Watermarking linear predictive coding Wavelet domain Discrete wavelet transforms Frequency Bit error rate Filtering algorithms Robustness Low pass filters Digital audio players

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Wideband speech coding advances in VMR-WB standard

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2007年第4期15卷 1167-1179页

作者： Jelinek, Milan Salami, Redwan Univ Sherbrooke Dept Elect & Comp Engn Sherbrooke PQ J1K 2R1 Canada VoiceAge Corp Montreal PQ H3R 2H6 Canada

This paper presents novel techniques for source-controlled variable-rate wideband speech coding. These techniques have been used in the variable-rate multimode wideband (VMR-WB) speech codec recently selected by the Third-Generation Partnership Project 2 (3GPP2) for wideband (WB) speech telephony, streaming, and multimedia messaging services in the cdma2000 third-generation wireless system. The codec utilizes efficient coding modes optimized for different classes of speech signal including generic coding based on AMR-WB for transients and onsets, voiced coding optimized for stable voiced signals, unvoiced coding optimized for unvoiced segments, and comfort noise generation for inactive segments. Several innovations enable very good performance at average bit rates below 8 kb/s for active speech coding. The article presents an overview of the codec and describes in detail some of the codec novel features: Robust pitch tracking algorithm, coding-mode dependent prediction of linear prediction (LP) filter quantization, and novel frame erasure concealment techniques including supplementary information for reconstruction of lost onsets and improving decoder convergence. Selected results from the Selection and Characterization tests of the codec illustrate its performance.

关键词： linear predictive coding standardization variable-rate speech coding wideband speech coding

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A speech-and-speaker identification system: Feature extraction, description, and classification of speech-signal image

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2007年第2期54卷 887-897页

作者： Saeed, Khalid Nammous, Mohammad Kheir Bialystok Tech Univ PL-15351 Bialystok Poland

This paper discusses a speech-and-speaker (SAS) identification system based on spoken Arabic digit recognition. The speech signals of the Arabic digits from zero to ten are processed graphically (the signal is treated as an object image for further processing). The identifying and classifying methods are performed with Burg's estimation model and the algorithm of Toeplitz matrix minimal eigenvalues as the main tools for signal-image description and feature extraction. At the stage of classification, both conventional and neural-network-based methods are used. The success rate of the speaker-identifying system obtained in the presented experiments for individually uttered words is excellent and has reached about 98.8% in some cases. The miss rate of about 1.2% was almost only because of false acceptance (13 miss cases in 1100 tested voices). These results have promisingly led to the design of a security system-for SAS identification. The average overall,success rate was then 97.45% in recognizing one uttered word and identifying its speaker, and 92.5% in recognizing a three-digit password (three individual words), which is really a high success rate because, for compound cases, we should successfully test all the three uttered words consecutively in addition to and after identifying their speaker;hence, the probability of making an error is basically higher. The authors' major contribution to this task involves building a system to recognize both the uttered words and their speaker through an innovative graphical algorithm for feature extraction from the voice signal. This Toeplitz-based algorithm reduces the amount of computations from operations on an n x n matrix that contains n(2) different elements to a matrix (of Toeplitz form) that contains only n elements that are different from each other.

关键词： communication humatronics linear predictive coding processing and recognition speaker recognition speech analysis Toeplitz matrix (TM) eigenvalues understanding speech

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Codebook-based Bayesian speech enhancement for nonstationary environments

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2007年第2期15卷 441-452页

作者： Srinivasan, Sriram Samuelsson, Jonas Kleijn, W. Bastiaan Royal Inst Technol Dept Signals Sensors & Syst SE-10044 Stockholm Sweden

In this paper, we propose a Bayesian minimum mean squared error approach for the joint estimation of the short-term predictor parameters of speech and noise, from the noisy observation. We use trained codebooks of speech and noise linear predictive coefficients to model the a priori information required by the Bayesian scheme. In contrast to current Bayesian estimation approaches that consider the excitation variances as part of the a priori information, in the proposed method they are computed online for each short-time segment, based on the observation at hand. Consequently, the method performs well in nonstationary noise conditions. The resulting estimates of the speech and noise spectra can be used in a Wiener filter or any state-of-the-art speech enhancement system. We develop both memoryless (using information from the current frame alone) and memory-based (using information from the current and previous frames) estimators. Estimation of functions of the short-term predictor parameters is also addressed, in particular one that leads to the minimum mean squared error estimate of the clean speech signal. Experiments indicate that the scheme proposed in this paper performs significantly better than competing methods.

关键词： Bayesian codebooks linear predictive coding noise estimation speech enhancement speech processing Wiener filtering

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Transmitter precoding with reduced-complexity soft detection for MIMO systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2007年第3期6卷 817-821页

作者： Li, Yong Moon, Jaekyun Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

We present a precoded reduced-complexity soft detection (PRCSD) algorithm for multiple-input multiple-output (MIMO) systems. The linear operations at both transmit and receive sides based on complex Householder transform convert the MIMO channel to be multiple-diagonal, spatially partial-response-like, so that error propagation is alleviated when applying reduced-complexity soft detection at the receiver. The transform results in unitary precoding and feedforward matrices so that neither transmit power boost nor noise enhancement is present. Performance analysis based on pairwise error probability (PEP) shows that PRCSD achieves larger diversity advantage than existing precoding and multiple-beamforming (MB) schemes, which basically attempt to transmit signals through diagonal independent sub-channels and thus may suffer a diversity loss. PRCSD can achieve full diversity as maximum likelihood (ML) detection in some scenarios while reducing complexity significantly.

关键词： linear predictive coding

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Statistical method for sparse coding of speech including a linear predictive model

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2006年第367期367卷 231-251页

作者： Rufiner, Hugo L. Goddard, John Rocha, Luis F. Torres, Maria E. Univ Nac Entre Rios Fac Ingn RA-3100 Oro Verde Entre Rios Argentina Univ Autonoma Metropolitana Iztapalapa Dept Ing Elect Mexico City DF Mexico Univ Buenos Aires Fac Ingn RA-1053 Buenos Aires DF Argentina

Recently, different methods for obtaining sparse representations of a signal using dictionaries of waveforms have been studied. They are often motivated by the way the brain seems to process certain sensory signals. Algorithms have been developed using a specific criterion to choose the waveforms occurring in the representation. The waveforms are choosen from a fixed dictionary and some algorithms also construct them as a part of the method. In the case of speech signals, most approaches do not take into consideration the important temporal correlations that are exhibited. It is known that these correlations are well approximated by linear models. Incorporating this a priori knowledge of the signal can facilitate the search for a suitable representation solution and also can help with its interpretation. Lewicki proposed a method to solve the noisy and overcomplete independent component analysis problem. In the present paper we propose a modification of this statistical technique for obtaining a sparse representation using a generative parametric model. The representations obtained with the method proposed here and other techniques are applied to artificial data and real speech signals, and compared using different coding costs and sparsity measures. The results show that the proposed method achieves more efficient representations of these signals compared to the others. A qualitative analysis of these results is also presented, which suggests that the restriction imposed by the parametric model is helpful in discovering meaningful characteristics of the signals. (c) 2005 Elsevier B.V. All rights reserved.

关键词： speech analysis and representation sparse coding linear predictive coding basis pursuit matching pursuit independent component analysis

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DSP restoration techniques for audio

DSP restoration techniques for audio

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IEEE International Conference on Image Processing (ICIP 2007)

作者： Moorer, James A. Adobe Syst Inc San Jose CA 95110 USA

ISBN: (纸本)9781424414369

The CD revolution of 1984 unleashed a massive campaign of rerelease of vintage analog recordings. To their collective horror, record labels found that many of the original master recordings had deteriorated. Often the only existing copy of a recording was a vinyl pressing. This rush to release beloved music in the new digital form spawned intense interest in digital methods of restoring these old recordings. A number of DSP techniques have been developed to give new life to these recordings. This paper is a survey of some of those methods.

关键词： music signal restoration signal processing linear predictive coding Wiener filtering

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