Showing papers on "Cepstrum published in 1987"

Some properties of the multidimensional complex cepstrum and their relationship to the stability of multidimensional systems

Abstract: Conditions are obtained for the cepstrum of anl1 sequence having arbitrary support on theM-dimensional lattice to exist also as anl1 sequence with arbitrary support. These conditions are used to show that the cepstrum of a sequence with support on a half-space will, when it exists, also have support on the same half-space. This result is used, in turn, to describe the support of the cepstrum of a sequence with bounded support on a half-space. The relationship between the existence of the cepstrum and bounded-input, bounded-output (BIBO) stability for all three of these cases is considered. Finally, the derivatives of the inversion operator, the homomorphic transform operator, and its inverse are calculated. These results are also useful in the one-dimensional case.

Pattern feature extracting system

Abstract: In a speech signal processing system for transmission or recognition, cepstrum data is normalized by subtraction from its straight-line approximation. As a result, personal and transmission characteristics are eliminated, and both data and subtraction computations are reduced.

Signal delay and waveform estimation through differential cepstrum averaging

Abstract: The differential cepstrum (DC) was introduced as a new tool for homomorphic deconvolution, a method which possesses the shift invariant property. The delay in the time samples will effect only the second sample of the DC. This property of the DC is used for estimating the signal delay and the waveform, in the presence of signal jitter and noise. Simulation results are presented to demonstrate the applicability of this technique for processing the signals embedded in white Gaussian noise. Better noise suppression has been observed through DC averaging as compared to group delay averaging or unwrapped phase averaging methods.

Nonminimum phase system identification via cepstrum modeling of higher-order cumulants

Abstract: A new computationally efficient identification procedure is proposed for a non-Gaussian white noise driven linear, time-invariant, non-minimum phase system. The method is based on the idea of computing the complex cepstrum of higher-order cumulants of the system output. In particular, the differential cepstrum parameters of the system's impulse response are computed directly from higher-order cumulants via least-squares solution. The method is flexible enough to reconstruct the minimum and maximum phase components of the impulse response of MA, AR or ARMA systems without any prior knowledge of the type of the system. It does not require model order selection criteria and is shown to provide estimates with small bias and variance even with "short" length data records.

A VQ-based preprocessor using cepstral dynamic features for large vocabulary word recognition

Abstract: This paper proposes a new VQ (Vector Quantization)- based preprocessor for use in a method which reduces the amount of computation necessary in speaker-independent large vocabulary isolated word recognition. A speech wave is analyzed by time functions of instantaneous cepstrum coefficients and short-time regression coefficients for both cepstrum coefficients and logarithmic energy. A universal VQ codebook for these time functions is constructed based on a multi-speaker, multi-word database. Next, a separate codebook is designed as a subset of the universal codebook for each word in the vocabulary. These word-specific codebooks are used for front-end preprocessing to eliminate word candidates whose distance scores are large. A dynamic time-warping processor based on a word dictionary, in which each word is represented as a time-sequence of the universal codebook elements (SPLIT method), then resolves the choice among the remaining word candidates. Effectiveness of this method has been ascertained by recognition experiments using a database consisting of words from a vocabulary of 100 Japanese city names uttered by 20 male speakers.

Implementation of an acoustical front-end for speech recognition

Abstract: We describe the implementation of a programmable general-purpose acoustical front-end for speech recognition; its design keeps into account, as an example, the algorithm of centisecond cepstrum extraction for an acoustical signal sampled at a maximum rate of 12.8 kHz.

A new automated method for reliable speaker identification and verification over telephone channels

Abstract: Notwithstanding the wide use of fully automatic method of feature extraction in speaker identification/verification tasks, based mainly on LPC, cepstrum and spectral band techniques, a recent work [1] by the authors demonstrated that in forensic applications semiautomatic, operator-assisted feature extraction procedures are more reliable. The drawbacks of a semiautomatic parameters extraction is either on the loss of real time or in the dipendence of the system performance on the skilled operator contribution. The proposed method of automatic parametrization of the speech signals seems to resolve these problems. Given the speech signal defined as a single realization of the speaker's voice, an automatic vowel identifier based on energy, pitch and cepstrum information provides the first segmentation. Then a formant trajectories tracer is operated and a rule-based system selects the suitable and stable frames on the vowels avoiding double sounds and transients. The restricted population of vowel-like sound frames is then subjected to a clustering procedure on the F1/F2 plane when all the a-priori knowledge on the vowel sounds is a guide to select the best five clusters to assign to the five Italian vowels. After the vectorization of the whole talker set and of the unknown veices, if any, the Bayes classifier is invoked and the proper decision tests are performed. The results of this automated extraction/decision sequence are presented in the paper with comparison to the oparator dependent procedure.

Consonant recognition methods for unspecified speakers using bpf powers and time sequence of LPC cepstrum coefficients

Abstract: This paper discusses the recognition of the consonant (except the consonant at the top of the word) in a word for unspecified speakers. First, the consonant section is detected based on the power dips extracted from the low- and high-frequency power information, together with the nasal and unvoiced properties. Applying the discrimination diagram to the detected low- and high-frequency dips, the phoneme is classified into the four phoneme classes (rough classification). Then methods are discussed which discriminate the individual phonemes in the phonemes group by pattern matching (fine classification). Using the time-series pattern of the LPC cepstrum coefficient as the parameter, it is shown that the comparison with the standard phoneme patterns using the Bayes' discriminant and the Mahalabinos distance is the most useful. The result of recognition experiment using the segmentation, rough classification, and fine classifications is presented. For twenty subjects of both sexes, the mean recognition rate of 78.1 percent was achieved.

4 - Analyse cepstrale en contrôle non destructif des milieux hétérogènes

Abstract: A new direction for the non destructive evaluation of heterogeneous materials is presented, which relies on the cepstrum of the backwards diffused signal for the characterization of the internat structure of the medium under study . The spectrum of the reflected signal is correlated to the sample structure . By using the cepstrum transform, informations about the mean spacing between the scatterers and the volume percent of heterogeneites may be obtained for biphase media . A set of simulations make the advantages of the cepstrum analysis over the spectral analysis clear . The theoretical results are compared with experiments.

Implementation of SAW complex cepstrum and its applications

Abstract: Implementation of the Complex Cepstrum (CC) and its inverse, using processors based on surface acoustic waves (SAW) devices, is presented. Design considerations based on theoretical analysis are given. The performance of the processor, partly built and totally simulated, is demonstrated as applied to recovering of a signal corrupted by multipath echoes.

Bearing detector for sound source by cepstrum analysis

Abstract: PURPOSE:To achieve a higher S/N ratio, by a method wherein sound waves of a sound source are received with a set of linear type equi-space receiver arrays to convert a time difference between received signals into a pulse interval signal and the bearing of a sound source is detected based on pitch information as obtained from a cepstrum analysis. CONSTITUTION:When sound waves of a sound source come to linear type equi- space receiver arrays 3 and 4 from the directions of thetaA, and thetaB, the arrays 3 and 4 separately output received signals sequentially. As the received signals exceed a fixed level, first and second pulse generation circuit 6A and 6B output pulses with a width (t) at a rising part of the received signals. The outputs of the pulses with the width (t) are added up with first and second pulse signal generation circuits 8A and 8B to make a continuous series of pulse interval signals. The pulse interval signal is repeated specified times with first and second pulse interval signal repeating circuits 9A and 9B according to the stability of the pulse interval thereof and then, subjected to cepstrum analyses 10A and 10B. As a result, pitch information on the received signals is obtained to calculate 11 bearing angles thetaA and thetaB and the bearing angles of the sound source are displayed 12.

Bearing detection in the presence of two sources of varying coherence using the complex cepstrum

Abstract: The effect of the presence of two acoustic sources (one, the primary, whose location is to be detected) of varying coherence on a cepstral bearing finding procedure is experimentally studied. The coherence between the acoustic sources was altered by adding random noise of various SNR (signal-to-noise ratio) to the input signal of the primary source; the same base signal being fed to both sources. The results demonstrate that, when block liftering is used, the primary source bearing is reliably estimated for coherences as low as gamma sup 2 greater than or approx equal to 0.5. The results also imply that background noise (unreflected) of SNR greater than or approx equal to 10 dB will not markedly affect the accuracy of the bearing estimation algorithm.

Vector quantization of speech signals using principal component analysis

Abstract: A new method of designing a vector quantizer is presented for bandwidth compression of speech signals, and some experimental results are shown. In this method, spectral parameters are extracted first from the DFT spectrum of input speech signals using a psychological frequency scale-the so-called Mel scale. This parameter is called the Mel-scaled spectrum. The number of Mel-scaled spectrum is reduced and the cepstrum of this parameter is calculated. Then this Mel-scaled cepstrum is vector quantized and the codebook-vector of the vector quantizer is determined by the algorithm using principal component analysis. With this algorithm, codebook-vectors can be designed considering the statistical characteristics of the Mel-scaled cepstrum. Also, the reduction of parameters by Mel-scale can decrease the size of the codebook memory without greatly degrading the synthesized speech quality. Using the forementioned method two codebooks are designed: one contains 256 vectors, and the other contains 2048 vectors. The quantization error is compared with those designed by the well-known LBG algorithm. The simulation results show that the codebooks designed by the proposed method present less quantization error and degradation of synthesized speech quality than those designed by LBG algorithm.

Application of the complex cepstrum to the location of acoustic sources near reflective surfaces

Abstract: The complex cepstrum is used to correct bearing estimations of acoustic sources in the presence of a reflective surface. An automated liftering procedure is used which zeros out a block portion of the cepstrum including the echo information. The problem of the resulting distortion is alleviated by applying a coherence criterion to the recovered direct signals at each microphone. Thus to a large degree the interactive nature of cepstral processing is overcome for this application. For the test signals and geometries considered the cepstrum is shown to accurately correct for bearing errors in acoustic signals contaminated with reflections from nearby surfaces.

Digital signal processing algorithms for automatic voice recognition

Abstract: The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.