In this letter, we propose a new auditory distance rendering (ADR) algorithm based on the interchannel phase difference (ICPD) control. In the conventional ICPD control, distance perception of the sound image is nonlinearly controlled, and directional localization of the sound image can be biased by changes of the interaural cues. These problems are caused by applying the frequency-independent ICPD without considering the acoustic transfer paths of the system setup. To solve these problems, first, the interaural cues of ear signals are analyzed by binaural auditory simulations. Then, stereophonic ADR filters are designed that produce ear signals with a linearly controlled interaural cross-correlation (IACC) and a consistent interaural level difference (IALD) for sophisticated distance perception under the given stereo setup. Subjective test results show that the proposed algorithm can provide better distance controllability than the conventional method with reduced lateralization blur of the sound image.

The conventional target power density spectrum (PSD) estimation methods based on the signal prediction inherently produce a biased target PSD because of irrelevant assumptions for the noisy environment. In this paper, an unbiased target PSD is obtained by removing the effect of diffuse noise on the prediction filter. In addition, by on-line estimation of both the noise PSD and target transfer function ratio (TFR) from the input signals, the proposed algorithm achieves robust noise suppression for an unknown target direction under a fast time-varying noisy environment. Computer simulations demonstrate the effectiveness and superiority of the proposed algorithm over the conventional methods.

This letter describes a numerical algorithm for synthesizing optimal low-sidelobe beampatterns. The pattern synthesis problem is formulated as a constrained optimization that minimizes the spatially weighted energy arriving at the array subject to unit gain in the look direction and a constant sidelobe level. The weighting takes on the form of a sensor correlation matrix, parameterized between uncorrelated sensor noise and correlated signal arrival terms according to a balancing factor. Setting the balancing factor to its extreme values of 0 and 1, produces, respectively, the optimal Riblet-Chebyshev and Delay-and-Sum type beamformers. In between, the method generates a low-sidelobe beamformer with varying beamwidths that provides a trade-off between White Noise Gain and Directivity Index. Simulation examples demonstrate optimal and intermediate designs for uniform and non-uniform sensor spacings.

The gradient adaptive lattice (GAL) algorithm is very attractive choice for active noise control of multiple sinusoidal interferences. In the GAL algorithm, a selection of step-size parameters trades off between convergence speed and steady-state performance. In this paper, we develop a variable step-size scheme for the filtered-x GAL (VSS-FxGAL) algorithm. This proposed algorithm achieves a good compromise between fast convergence speed and low steady-state mean-square error (MSE). In addition, comparing to the filtered-x affine projection (FxAP) algorithm, the proposed algorithm performs better when the filter input consists of multiple sinusoids.

This paper proposes an improved phase parameter analysis and synthesis method for parametric stereo audio coding. For stereo signal with low interchannel coherence (IC), conventional phase parameter analysis and synthesis methods show poor quality, since they overlook the effect of IC to the phase parameters defined. The proposed system defines new phase parameters reflecting IC information, so that we can alleviate the deterioration of audio quality due to the synthesis of excessive phase difference, especially when IC is low. Subjective listening test results are presented to show that the proposed method provides always better audio quality than the conventional methods.

This paper presents a mathematical analysis of the effects of interchannel amplitude and time differences in two channel (stereophonic) sound systems. The analysis is developed by computing the acoustic conditions at the listener's ears as a function of the stereophonic signal feature. We also present separate approximations of head-related transfer function (HRTF)-based panning according to predefined frequency bands. We attempt to create non-sophisticated models of the stereophonic listening mechanism with approximations in both the time and frequency domains. The models are based upon psychoacoustical theories that present the frequency-dependent relative importance of acoustical cues. Based on the model, we propose new panning methods that can enhance the localization accuracy of conventional panning methods, such as amplitude panning and HRTF-based panning. The localization performances of the new panning techniques are evaluated and compared by means of auditory model simulations and listening tests. Through simulations and listening test results, it is shown that the proposed panning method makes substantial improvements in the localization of virtual sources.

In this paper, we propose a method of restoring principal to ambient energy ratio (PAR) at the decoder in the principal component analysis (PCA)-based parametric audio coding. The conventional approach applies the post-scaling at the decoder using the energy information extracted from the input signal at the encoder. However, this approach has a problem that the relative energy of principal source in the reconstructed signal is smaller than the original signal and also affected by the panning angle of principal source. To restore the PAR at the decoder, the proposed method estimates the post-scaling factors using parametric information extracted from PCA-based formulation. The objective and subjective results verify the performance improvement of proposed method.

In this paper, we propose an audio transcoding algorithm for mobile multimedia applications. The algorithm is to provide high quality transcoded audio stream from a multimedia broadcasting media server system to mobile terminals. As a representative case, audio transcoder between T-DTV and T-DMB service is considered. While the Korean DTV audio standard adopted the Dolby AC-3, the Korean T-DMB service uses the MPEG-4 BSAC. The proposed algorithm reuses the bit allocation information of the AC-3 decoder in the process of BSAC encoding and simplifies the bit-allocation process with two independent loops instead of nested ones. We verified that our architecture could take the place of the nested loop with a significant simplification and no PAM. The proposed audio transcoding algorithm is suitable for the mobile multimedia applications due to its low complexity and minimum frame-by-frame complexity variations.

This paper proposes a novel speaker identification system based on score fusion of various resolution filterbanks. The proposed system uses multiple features which are extracted from filterbanks having various spectral resolutions. Each speaker model is constructed by independent feature set, but the system makes final decision by combining the outcome of each model. We introduce several well-known voting methods for decision. Simulation results using TIMIT database show that the proposed score fusion method significantly improves speaker identification performance compared to single model one. Especially, 59.28% of relative improvement is achieved by using a product rule.

A noise-robust pitch synchronous feature extraction algorithm for speaker recognition systems is proposed in this paper. Since the pitch synchronous algorithms utilize pitch information, which is meaningful only for periodic segments, we propose a new scheme to deal with non-periodic ones such as unvoiced and noise-corrupted. The experimental results show that the proposed algorithm outperforms the conventional algorithm us- ing fixed length of analysis window in actual identification tasks even in low SNR noisy environments.

The paper describes important issues on transcoding between different speech codecs by considering the paradigms of source and target coders. Conventional transcoding algorithms on LSP, pitch and adaptive/fixed codebook conversion are refined with regard to the structure of the coders. In addition, a new perceptual weighting filter, that plays a role in the post-filter and perceptual weighting filter together, is proposed to improve the performance further. The performance of the proposed algorithms is verified in a step-by-step manner with examples of transcoding between AMR, G.723.1 and G.729. By applying the proposed algorithm to the transcoders, the complexity is reduced by about 20-76.88% and quality is also improved compared to conventional approaches.

The paper presents a novel feature extraction method to improve the performance of speaker identification systems. The proposed feature has the form of a typical conventional feature, Mel frequency cepstral coefficients (MFCC), but a flexible segmentation to reduce spectral mismatch between training and testing processes. Specifically, the length and shift size of the analysis frame are determined by a pitch synchronous method, pitch synchronous MFCC (PSMFCC). To verify the performance of the new feature, we measure the cepstral distortion between training and testing and also perform closed set speaker identification tests. With text-independent and text-dependent experiments, the proposed algorithm provides 44.3% and 26.7% relative improvement, respectively.

In this paper we present an efficient coding method for the upper band(4-7kHz) of wideband(0.5-7kHz) speech coding based on a band-split approach. Due to the impulselike characteristics in upper band signal, it is very difficult to efficiently quantize the signal at low bit-rate when we use transform coding techniques. We propose two temporal normalization techniques, direct temporal energy normalization and frequency domain linear prediction, to reduce the extremely noticeable artifacts. Simulation results show that the proposed algorithm successfully encodes the upper band signal, and the new split-band type wideband coder adopting the proposed technology provides better quality than 56 kbit/s ITU-T G.722 at the bitrate of 20 kbit/s.

This paper presents a cascade structure of an algebraic codebook to improve the performance of low bit-rate speech coder. A codeword of an algebraic codebook consists of a set of pulse amplitudes and positions. In general, the amplitude of each pulse is constrained to be either +1 or -1 due to the limitations of bit-rate and complexity. Thus, the performance of the codebook is varied depending on the characteristic of input target vectors. In this paper, we extend the algebraic codebook structure to two stages in order to provide flexible pulse combinations. While all pulses, M, are simultaneously selected in a classical one-stage algebraic codebook, the cascade structure searches the pulses with a two step procedure, i.e., L pulses at the first stage and (M-L) pulses at the second stage. Experiments confirm that our algorithm provides higher quality than the conventional scheme when the total number of pulses is same. In case of assigning 24 pulses per 8-ms subframe, a segmental SNR between target and synthesized signal increases 1.04 dB. In addition, at the same environment, the complexity of fixed codebook search is reduced by about 32%.

We propose a packet loss concealment algorithm for a code-excited linear prediction (CELP) speech coder. We perform a time-scale modification (TSM) using a waveform similarity overlap-add (WSOLA) technique to reconstruct the excitation signal of the lost or dropped frames. In addition, when a lost frame is classified as a voiced, an adaptive codebook gain and a fixed codebook gain are estimated by a modified gain parameter re-estimation (GRE) technique. By applying these techniques, we can reduce quality degradation of the decoded speech and error propagation effect through the adaptive codebook memory. We apply the proposed scheme to the ITU-T G.729 standard speech coder to evaluate the performance of the proposed method. The perceptual evaluation of speech quality (PESQ) and AB preference tests under various packet loss conditions verify that the proposed algorithm is superior to the concealment algorithm embedded in the G.729.

In MIMO-OFDM systems, a conventional channel estimation technique using comb type training symbol structure has high mean squared error (MSE) at edge subcarriers. To reduce the MSE at those subcarriers, we propose the cyclic comb type training structure and the weighted-averaging method. In the proposed technique, all kinds of comb type training symbols are transmitted cyclically at each transmitter. At the receiver, channel frequency responses estimated using each training symbol are averaged with weight which is obtained from the corresponding MSE. By computer simulations, we have shown that the proposed cyclic comb type training symbols gives higher SNR gain than the conventional training structure.

In this paper, a discrete multitone (DMT) modem for the client side G.LITE ADSL transceiver is presented. The DMT modem is one of the most computationally intensive parts in the transceiver. In the design, computational complexity and operational regularity were traded-off to decide suitable fast Fourier transform (FFT)/Inverse FFT and frequency-domain equalization (FEQ) algorithms. We used the radix-2 real FFT and the normalized LMS that guarantees an equal convergence per tone. Based on operational community between FFT and FEQ, a resource-shared design was implemented. Datapath of the DMT modem comprises one real multiplier and two real adders, which are connected in parallel and flexibly used under control. The designed modem has been coded in VHDL and synthesized with 0.35-/spl mu/m standard CMOS cell. Synthesis results exhibit that the proposed system can provide a cost-effective solution to asymmetric digital subscriber line devices owing to its small design area.

In this paper, we present a highly optimized one-chip digital audio decoder supporting both MP3 and AAC standards. The design has been focused on the hardware modularity for both MP3 and AAC. The hardware consists of a Huffman decoder module and 20-bit programmable DSP module. In addition, a hardware module for the prediction tool of AAC has been added to support AAC Main Profile. Utilizing the modularity of the designed hardware, MP3 and AAC decoding algorithms are distributed to each module in such a way that the system resource can be maximally utilized. The designed system can decode MPEG/Audio layer-3 bitstream using only 13.33 MIPS and MPEG-2 AAC Main Profile bitstream using only 16.9 MIPS while the high accuracy of the decoded output PCM can be obtained with it.

In this paper, we present a new bandwidth-scalable coder for wide band speech and audio signals. The proposed coder splits 8 kHz signal bandwidth into two narrow bands, and different coding schemes are applied to each band. The lower-band speech is coded with ITU-T G.729 Annex E, and the higher-band signal is compressed using a new algorithm based on the gammatone filter band with an invertible auditory model. Due to the split-band architecture and completely independent coding schemes for each band, the output speech of the decoder can be selected to be a narrowband or wideband coding according to the channel conditions. Subjective tests showed that, for wideband speech and audio signals, the proposed coder at 18 kbit/s produces superior quality to ITU-T 24 kbit/s G.722.1 with the shorter algorithmic delay.

A residual echo cancellation scheme based on the autoregressive (AR) analysis is proposed for hands-free telephony. Residual echo is whitened by the inverse filter using the estimated AR coefficients. Removing the speech characteristics of the residual echo signal, the noise reduction system successfully reduces the power of residual echo as well as that of ambient noise. In a car cabin, the proposed method improved the echo return loss enhancement by 8.7/spl sim/9.9 dB as compared with the conventional combined system.

A system architecture optimized for the 2-channel main-profile MPEG-2 AAC decoder is presented. In order to enable an efficient job scheduling and allocation, the presented system comprises three hardware modules: Huffman decoder module, predictor module, and processing core module which is programmable using an assembly language of its own. The Huffman decoder is designed to finish the requested job in only 1 clock cycle time and the predictor forms parallel processing with other modules, so that utilization of the system resource is maximized. The developed system has been coded in VHDL and the MPEG-2 AAC decoding algorithm is programmed using the assembly language of the processing core. For the verification of the decoding algorithm, the 16-bit PCM output of the system was compared with the result of the floating-point simulation, and the result showed the maximum of 2-bit difference. Functional simulation verified that the developed system can decode standard MPEG-2 AAC main-profile bitstreams in real-time with high accuracy.

Echo watermarking marks audio signals by adding an echo. The embedded signal is not additive noise but an audio signal having the same statistical and perceptual characteristics. The echo is even perceived as added resonance. Conventional echo watermarking techniques often exhibit inherent trade-offs between imperceptibility and robustness. A new echo embedding technique is proposed. The proposed method enables one to embed high energy echoes while the host audio quality is not deteriorated, so that it is robust to common signal processing modifications and resistant to tampering. This is possible due to echo kernels that are designed based on psychoacoustic analyses. Subjective and objective evaluations confirmed that the proposed method could improve the robustness without perceptible distortion.

An integrated acoustic echo and noise cancellation system for hands-free telephony is presented. The proposed system includes a new residual echo cancellation scheme based on spectral analysis and a new double-talk detector suitable for real-time implementation. Residual echo is whitened via AR analysis during no near-end-talk period and is cancelled by noise reduction. Removing speech characteristics of the residual echo signal, noise reduction successfully reduces the power of the residual echo as well as the ambient noise. For further integration with commercial low-bit rate speech coders, noise reduction in IS-127 (EVRC) was considered. For the hands-free situation in the moving car, the proposed system attenuated the interferences more than 30 dB at a constant speed of 90 km/h. The proposed system was implemented on a low-cost DSP with 16-bit fixed-point arithmetic.

A new echo embedding technique in audio watermarking is proposed. The proposed method enables one to embed large energy echoes while the host audio quality is not deteriorated, so that it is robust to common signal processing modifications and resistant to tampering. Practical issues such as parameter tuning and further schemes for robust detection under attacks are also described. Subjective and objective evaluations confirmed that the proposed method could improve the robustness without perceptible distortion.

Dual-rate G.723.1 speech coder has been widely applied to real-time video and teleconferencing applications where reduced bandwidth and good voice quality is required. This paper presents an efficient implementation of G.723.1 speech coder. To simplify the excitation quantization procedure which is the most computationally demanding, we propose fast algorithms for adaptive codebook and fixed codebook search. In the fast adaptive codebook search, pitch delay and pitch gains are computed sequentially. In the fast fixed codebook search, the codebook structure is redesigned based on the interleaved single-pulse permutation (ISPP) design at high rate mode and the depth-first tree search is applied instead of nested-loop search at low rate mode. A real-time implementation is achieved using a 16-bit fixed-point TMS320C62x DSP. The implemented G.723.1 speech coder requires 8.70 and 10.29 MHz clock cycles at low and high rate, respectively, 57.8 kByte of program memory and 55 kByte of data memory. Thus, more than 16 channels of G.723.1 coder can be operated in real-time using a single TMS320C62x DSP.

Interoperability is one the most important factors for a successful integration of the speech network. To operate speech networks employing different speech coders, but integrated as one, bitstreams generated by one coder should be translated seamlessly to those of the other coders. Connecting two coders in tandem may be the simplest way to accomplish this. However, coders in tandem connection often produce problems such as poor speech quality, high computational load, and additional transmission delay. We propose an efficient transcoding algorithm that can provide interoperability to the networks employing ITU-T G.723.1 and TIA IS-127 EVRC speech coders. Subjective and objective quality evaluation have confirmed that the speech quality produced by the proposed transcoding algorithm was equivalent to, or better than the tandem coding, while it had shorter processing delay and less computational complexity.

This paper proposes an LMS (least mean squares) based forward-link beamforming method. The proposed forward-link beamforming system compensates the phase distortion of reverse-link channel states for reverse-link LMS weight. Therefore, no additional beamforming module for forward-link beamforming is required for the proposed system. While performance of the proposed system is comparable with the conventional forward-link beamforming system, complexity of the proposed system is much less than the conventional system.

In this paper, we present an efficient noise control algorithm based on the delayless subband adaptive filter. The algorithm reduces the computational complexity of the delayless subband filter by decomposing the secondary path response into a set of subband functions. In this new algorithm, the filtered reference signal is generated for each subband by using a short impulse response filter that models the secondary path transfer function in a subband-decomposed form. Computational efficiency of the presented method originates from the fact that the filtering process occurs only in one subband for each reference input sample. Furthermore, computational efficiency is enhanced when the presented algorithm is combined with an online identification of the secondary path transfer function. We also propose a frequency-domain implementation of the presented algorithm. In this implementation, it is shown that the computational complexity is further reduced by employing the block-processing approach.

Stereophonic sound becomes more important in a growing number of hands-free applications where spatial realism is demanded. Such hands-free systems need stereophonic acoustic echo cancellers to reduce echoes that result from coupling between loudspeakers and microphones. In this paper, we propose a new adaptive algorithm for an stereophonic acoustic echo canceller based on human auditory properties and affine projection (AP) algorithm. The proposed algorithm employs a pre-processor generating speech-like noise to decorrelate the input signals without degrading perceptual speech quality. The decorrelation is based on the masking patterns of the human auditory system. By showing that the AP algorithm can be represented by a vector update as a combination of the Gram-Schmidt (GS) orthogonalization followed by the normalized LMS (NLMS) algorithm, the proposed adaptive algorithm integrates the pre-processor into the adaptive algorithm. Subjective listening test and computer simulation show the effectiveness of the proposed algorithm.

Since wavelet decomposition of signals provides more flexible time-frequency resolutions, it can be utilized as a feature set for speech recognition. The authors explore the possibility of using wavelet decomposition for speech recognition. In particular, they investigate a modified octave structured 5-level filter bank and the HMM (hidden Markov model) is used as a recognizer. We present an analysis of various wavelet filters for speech recognition and compare the results with the conventional features that include LPC and mel-cepstrums.

In this study, new implementation techniques of a real-time MPEG-2 audio encoding system are presented. The system is developed using general-purpose DSPs. It consists of one master unit and five slave units, and its structure is basically based on our early work [1]. Two fast algorithms are developed and applied to the most compute-intensive routines of the encoding process. These algorithms play a key role in improving the entire system performance. The implemented system is designed to encode audio signal into MPEG-2 layer II bitstream with full configurations up to 5.1 channels and 640 kbps, and intended to support state-of-the-art quality. The generated bitstream can be stored in a hard disk on a PC or sent to an integration system to be multiplexed with the corresponding video-bitstream.

A speaker adaptation algorithm using formant frequencies is proposed. The formants extracted from the cepstral means in the reference codebook are iteratively shifted toward the formants of a test speaker. The number of cepstral means selected at each iteration decreases as the iteration increases. The decision of the number of selected cepstral means and a formant based distance measure are formulated. The proposed algorithm was implemented in two schemes and evaluated by speaker-independent, male speaker dependent, and female speaker-dependent recognition experiments. A combined scheme with the Bayesian adaptation obtained 9.7% enhancement for the average recognition accuracy in speaker-independent experiments and 52.6% in speaker-dependent recognition experiments.

This paper presents an efficient adaptive predistortion technique compensating for nonlinear distortions caused by a high-power amplifier (HPA) cascaded with a linear filter in an OFDM system. In the proposed approach, the memoryless HPA, preceded by a linear filter with memory in OFDM systems, is modeled by the Wiener system, which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. It is confirmed by computer simulation that the proposed approach produces a faster convergence speed than the previous adaptive predistortion technique, and provides a small output backoff as low as 5.5 dB for an OFDM system employing an HPA with a linear filter.

This paper describes a block-by-block basis image enhancement algorithm which uses the signal subspace method to enhance images corrupted by uncorrelated additive noise. The enhancement is performed by eliminating the noise components in the noise subspace and estimating the clean image from the remaining components in the signal subspace.

Audio codec (coding/decoding) algorithms are complex, of several coding techniques, and can be divided into DSP tasks, controller tasks and mixed tasks. The traditional DSP processor has been designed for fast processing of DSP tasks only, but not for controller and mixed tasks. This paper presents a new architecture that achieves high throughput on both controller and mixed tasks of such algorithms while maintaining high performance for DSP tasks. The proposed processor: YSP-3, operates four functional units (multiplier, two ALUs, load/store unit) in parallel via 4-issue super-scalar instruction structure. The performance evaluation of YSP-3 has been done through the implementation of the common DSP algorithms and the AC-3 decoder.

This paper presents an optimum space-time moving target indication (MTI) processor for the airborne radar. The optimization is based on a stochastic target model, rather than deterministic target models adopted in most space-time MTI processor designs. The optimum solution that maximizes the improvement factor yielded by the processor is shown to be the generalized eigenvector corresponding to the smallest generalized eigenvalue of the signal and clutter covariance matrices. A suboptimal, but computationally simpler solution to this problem is also derived. This approach requires the solution of a linearly constrained minimum variance (LCMV) problem. Unlike typical LCMV problems, our solution also calculates the response vector specifying the frequency response along the look direction. Experimental results demonstrating the usefulness of our methods are included in the paper. The results indicate that the suboptimal solution does not suffer from significant performance loss.

A duration modeling scheme and a speaking rate compensation technique are presented for the HMM based connected digit recognizer. The proposed duration modeling technique uses a cumulative duration probability. The cumulative duration probability also can be used to obtain the duration bounds for the bounded duration modeling. One of the advantages of proposed technique is that the cumulative duration probability can be applied directly to the Viterbi decoding procedure without additional postprocessing. Therefore, it rules the state and word transition at each frame. To alleviate the problems due to fast or slow speech, a modification to the bounded duration modeling which accounts for speaking rate is described. The experimental results on Korean connected digit recognition show the effectiveness of the proposed duration modeling scheme and the speaking rate compensation technique.

In this paper, a new active noise control algorithm based on a delayless subband adaptive filter architecture is presented. Also, an on-line system identification method implemented in the subband structure is suggested. To implement the filtered-x LMS algorithm in the subband structure, the secondary path transfer function is decomposed into sets of subband functions. The two filter on-line modeling algorithm is then applied to each subband to estimate the secondary-path transfer function in a decomposed form. In this manner, the computational load for the on-line system identification is reduced by a factor 3 compared with the wideband approach. Simulation results are presented to show the efficiency of the new ANC algorithm and the performance of the on-line system identification scheme.

A new vector sum excited linear prediction (VSELP) speech coder employing mutually orthonormal regular pulse vectors is presented. Since the algorithm uses an efficient vector-sum codebook consisting of mutually orthonormal regular pulse basis vectors, computational load for codebook search can be significantly reduced, while the reconstructed speech quality is equivalent to that of the conventional VSELP. The method, referred to as regular pulse VSELP (RP-VSELP), employs the Gram-Schmidt (GS) procedure to orthonormalize the basis vectors designed in a form of regular pulses. To enhance the SNR performance, the basis vectors are optimized using an iterative closed-loop training process.

A newly developed image enhancement algorithm is described in this contribution. The proposed algorithm makes use of the signal subspace method to enhance images corrupted by uncorrelated additive noise. This enhancement is performed by eliminating the noise subspace and estimating clean image from the remaining signal subspace. We propose the block-adaptive Wiener filtering which engages properties of the human visual system to estimate clean image. This criterion enables one to not only preserve the detailed structure of the given image, but to reduce the level of background noise as well. Subjective evaluation tests show the superiority of the method proposed here. In particular, edge blurring effects are noticeably reduced compared to the conventional methods.

In this paper, we describe a voice transformation meth-od which c hanges source speaker's acoustic features to those of a target speaker.The method developed here, acoustic features are divided into two parts, linear and nonlinear parts.Linear parts are characterized by LPC cepstrum coecients which are obtained from LP analysis.As for nonlinear part, which represent the excitation signal, is modelled by the long-delay nonlinear predictor using a neural net.Conversion rules for excitation signal are generated by the average pitch ratio and the mapping codebook, and those for LPC cepstrum coecients are based on the orthogonal vetctor space conversion.In addition, the spectral envelope compensation is proposed to correct spectral distortion in the transformed speech.A listening test shows that the proposed method makes it possible to convert speaker's individuality while maintaining high quality.

The least mean square (LMS) algorithm employed in the transversal filter structure has been very popular due to its simplicity. It is, however, often inappropriate to use the LMS algorithm in the transversal filter for designing an acoustic echo canceller since the echo path is usually very long and the algorithm suffers from the slow convergence. Moreover, most echo paths change their characteristics frequently according to the room environment, and thus the algorithm and structure must be chosen carefully in order to allow tracking capability. The adaptive lattice filter is an excellent alternative to improve convergence speed since the lattice structure inherently has the orthogonalization property between the backward prediction errors, but at the expense of the excessive computational load. If the input signal to be used can be modeled as an autoregressive (AR) process (say, P-th order), the reflection coefficients of the lattice filter after stage P will approach asymptotically to zero. In this case, instead of using the full-size lattice structure, the structure may be implemented in conjunction with the transversal filter structure after the P-th stage. In this paper, we propose this new lattice/transversal joint (LTJ) structure, and investigate its performance. We have found that the convergence of this new LTJ structure is almost as fast as that of the full-size lattice filter, while it maintains the computational complexity as low as that of the full-size transversal filter.

Hidden Markov models (HMMs) with explicit state duration density (HMM/SD) can represent the time-varying characteristics of speech signals more accurately. However, such an advantage is reduced in relatively smooth state duration densities or long bounded duration. To solve this problem, the authors propose HMMs with global path constraint (HMM/GPC) where the transition between states occur only within prescribed time slots. HMM/GPC explicitly limits state durations and accurately describes the temporal structure of speech simply and efficiently. HMMs formed by combining HMM/GPC with HMM/SD are also presented (HMM/SD+GPC) and performances are compared. HMM/GPC can be implemented with slight modifications to the conventional Viterbi algorithm. HMM/GPC and HMM/SD+GPC not only show superior performance than the conventional HMM and HMM/SD but also require much less computation.>

An adaptive multichannel digital filter structure that can be used in multichannel noise-cancelling applications is described. The proposed structure is a hybrid of the lattice and the escalator (Gram-Schmidt) structures, and the coefficients are updated using the least-mean-square algorithm. In the lattice-escalator hybrid structure, complete decorrelation of multiple reference signals is achieved by successively generating forward prediction error vectors via the lattice structure and decorrelating the elements of the error vectors using escalator linear combiners at each lattice stage. Simulation results indicate that the convergence speed of the hybrid structure is as fast as the escalator realization.>

It is proposed to implement the linearly constrained adaptive array processor using multichannel lattice filter. Due to the Gram Schmidt orthogonalization properties of the lattice structure, the proposed realization converges faster and yields smaller estimation errors than the TDL counterpart. Computer simulation results comparing the performances of the mulichannel TDL and lattice filters for the linearly constrained adaptive array processing problem are presented.

An efficient method for updating the lattice filter/predictor coefficients using the sign algorithm is introduced. The pertinent coefficients are updated using only the signs of the estimation errors at each stage. This method requires less number of multiplications than other adaptive lattice filter algorithms. The performance of this method is compared with that of the lattice filter using the LMS algorithm for the problems of spectrum estimation and adaptive interference cancellation.

This paper introduces two recursive realizations of the Phase Transform (PHAT) processor for time delay estimation (TDE), using a simple one-pole lowpass filter and the least mean square (LMS) adaptive filter, respectively. It is shown that these adaptive methods are very effective in reducing the effect of interfering tonals. The performances of these methods are compared with those of other existing adaptive TDE algorithms via computer simulations.

Adaptive linear phase filters with the escalator [3] and triangular lattice [4,5] structures are proposed. Simulation results are also included to compare the performances of the proposed approaches with that of the tapped delay line filters for the problems of baseband channel equalization, when the relevant coefficients are updated using the LMS gradient method.

The main objective of this paper is to compare two adaptive algorithms for estimating the time delay between two-sensor outputs. These methods are very similar in the sense that they minimize the mean-squared error using a least mean square (LMS) gradient approach to estimate the time difference of arrival to two sensors. However, they apply the LMS gradient method in different ways, thereby holding different properties. Some theoretical aspects are addressed. Also, they are compared via computer simulations for a variety of cases, which include time-varying delay functions corresponding to moving source or receivers.

This paper concerns a study of some aspects of the SCOT (smoothed coherence transform) and Roth algorithms, which are useful for time delay estimation. The behaviour of the SCOT algorithm for the time delay estimation of sinusoids is investigated, and adaptive time domain implementations for the Roth and SCOT algorithms are presented.

This paper concerns an adaptive approach for estimateing the magnitude-squared coherence (MSC) function via Widrow's least-mean-square (LMS) algorithm. Some theoretical aspects are addressed, and simulation results are presented to evaluate the performance of the adaptive approach.

A method for generating a delayed version of a given bandlimited signal is presented, where the delay could be time-varying. Simulation results which illustrate the performance of this method are also included.

This paper presents a recurrence relation that enables one to obtain the inverse filter associated with an adaptive escalator predictor (AEP). The behaviour of this inverse filter is illustrated by means of a simple experiment related to the detection and frequency estimation of a sinusoidal burst embedded in band-limited noise.