LPC Spectrum Research Articles

VoxMore: artefato tecnológico para auxiliar a avaliação acústica da voz no processo ensino-aprendizagem e prática clínica

ABSTRACT Purpose to present a technological artifact, the VoxMore plugin, to assist the academic teaching of voice acoustic assessment, as well as to optimize the speech therapy intervention in the practice of vocal clinics. Methods this is a multidisciplinary methodological study for the development of a technological artifact, a plugin, to be used in the Praat software. This tool performs vocal acoustic analysis and generates a report, with information and images referring to the domains of time, frequency, time-frequency, and que-frequency, as well as values of acoustic measures related to fundamental frequency (f0), period measures, disturbance measures of the period of f0, f0 amplitude perturbation measurements, spectral measurements, glottal noise measurements and cepstral measurements. Results in the VoxMore acoustic report, four files are generated with the following information: oscillograms of the voice signal and traces of f0 and intensity; images related to the frequency domain, Fourier spectrum and LPC spectrum, and to the time-frequency domain, spectrogram; information on cepstral and cepstrogram analysis; the values of all acoustic measurements, in numerical results format and in vertical bar graphs. Conclusion VoxMore can contribute both to the teaching-learning process, acting as an auxiliary tool with a formative character in the undergraduate and graduate courses in Speech-Language Pathology, as well as to the clinical practice process, making the use of acoustic analysis in the vocal clinic feasible and supporting decision-making by speech-language pathologist.

A Study on the Characteristics Analysis of Presidential Voices in Four Countries using LPC Spectrum

A Study on the Characteristics Analysis of Presidential Voices in Four Countries using LPC Spectrum

Digital signals analysis with the LPC method

This paper concerns the issue of signal analysis by the linear predictive method. It is not only about frequency analysis, that is obtaining the LPC spectrum and comparing it with the Fourier one, but also about analysing prediction coefficients themselves. We will also discuss the program made by the authors of this paper, which beside foregoing functionalities, enables vocal tract visualization, modelled on the basis of LPC coefficients.

A new method of extracting the filter characteristics of the nasal cavity using homorganic nasal-stop sequences

This study attempts to derive the filter characteristics of the nasal cavity of individual speakers. Since the only difference between a nasal and a homorganic voiced stop, such as [mb] and [nd], is whether the passage to the nasal cavity is open or not, the subtraction of the LPC spectrum of the voiced stop from that of the preceding nasal leads to the filter characteristics of the nasal cavity of an individual speaker regardless of place of articulation. The results showed that the spectral differences between samples of 20 ms taken from the steady states of the nasal and the following voiced stop were close to constant regardless of place of articulation, representing characteristic poles and zeroes, and that the spectral differences varied with speakers. This study is significant in that it provides a new method of extracting the filter characteristics of the nasal cavity, and that the spectral difference between a nasal and a homorganic voiced stop can be used as a parameter of the filter characteristics of the nasal cavity of individual speakers.

Recursive coding of spectrum parameters

A theoretical analysis of recursive speech spectrum coding, where predictive and finite state schemes are special cases, is presented. We evaluate the spectral distortion (SD) theoretically and design coders that minimize the SD. The analysis rests on three cornerstones: high-rate theory, PDF modeling, and an approximation of SD. A derivation of the mean L/sub 2/-norm distortion of a recursive quantizer operating at high rate is provided. Also, the distortion distribution is supplied. The evaluation of the distortion expressions requires a model of the joint PDF of two consecutive spectrum vectors. The LPC spectrum source considered here has outcomes in a bounded region, and this is taken into account in the choice of model and modeling algorithm. It is further shown how to approximate the SD with an L/sub 2/-norm measure. Combining the results, we show theoretically that 16 bits are needed to achieve an average SD of 1 dB when quantizing ten-dimensional (10-D) spectrum vectors using a first-order recursive scheme. A gain of six bits per frame is noted compared to memoryless quantization. These results rely on high-rate assumptions which are validated in experiments. There, actual high-rate optimal coders are designed and evaluated.

Robust LPC spectrum quantization-vector quantization by a linear mapping of a block code

In this paper, we address the use of a vector quantizer (VQ) defined as a linear mapping of a block code (LMBC-VQ) in robust LPC spectrum quantization. Split VQ and multistage VQ of LSF's are considered. We demonstrate several properties for the LMBC-VQ including design methods and channel robustness theory. The LMBC-VQ codebooks are, guided by the robustness theory, directly designed with inherent robustness against channel errors. We demonstrate results where the resulting LMBC-VQ's outperform conventional codebooks designed with the generalized Lloyd algorithm in the presence of channel errors even when postprocessing index assignment is applied to the latter. Listening tests confirmed that the increased robustness is significant for the perceptual quality. We show that short block codes can be used to build the codebooks with no or small losses in quantization performance. This is advantageous for channel error robustness, lower memory requirement, and lower complexity. We also describe the structure of split VQ and multistage VQ using the LMBC framework. This allows us to assess the structural constraints and to generalize these VQ schemes, resulting in improved performance.

Time-frequency speech transformation based on an elementary waveform representation

A representation of the speech signal as a sum of elementary waveforms (Elementary Waveform Speech Model or EWSM) is introduced and some of its features for modifying localized time-frequency events are demonstrated. The elementary waveforms model the local spectro-temporal maxima of energy within the speech signal thanks to the use of simple mathematical functions. An automatic analysis-synthesis system allows for waveforms parameters estimation, using frame-by-frame processing: spectral modelling and segmentation using short-time Fourier transform and LPC spectrum, Fourier filtering according to this segmentation, waveform spotting in each channel, waveform modelling using simple functions. The classical theory of speech production proves the validity of the EWSM parameters; their modifications yield well-localized time-frequency transformations, including frequency compression/expansion, pitch, formant and noise modification.

Evaluation of a spectrum target prediction model in speech perception

A model of a spectrum target prediction mechanism is proposed and evaluated by comparing predicted values with results of psychoacoustic experiments. When the trajectory of the cepstrally smoothed LPC spectrum is approximated by a second-order critically damped system, the proposed model can estimate target values using short-period spectrum sequences (50 ms) without being given the onset positions of the spectral transition. Additionally, this model decreases the length of transitional sounds and recovers vowel characteristics neutralized by coarticulation. Moreover, this model compensates for the transitions of syllables and extracts stable characteristics from syllable transitions. This model is applicable to coarticulation recovery in speech signal processing.

On the performance of isolated word speech recognizers using vector quantization and temporal energy contours

The technique of vector quantization has been widely applied in the area of speech coding and has recently been introduced into the area of speech recognition. For the conventional statistical pattern recognition word recognizer using LPC feature sets as the analysis frames, the use of vector quantization leads to a large reduction in computation for the dynamic time warping pattern matching, and a concomittant small increase in average word error rate. A second technique that has been recommended for improving the performance of isolated word recognizers is the addition of temporal energy information into the distance metric for comparing frames of speech. It has been shown that the information in the prosodic energy contour complements the segmental information of the LPC spectrum, thereby providing small but consistent improvements in performance for small word vocabularies. In this talk we present results of a series of speaker independent, isolated word recognition tests using a 10-word digits vocabulary and a 129-word airlines vocabulary. We show the effects, on recognition accuracy, of adding both vector quantization and temporal energy in various combinations, to the recognition paradigm.

Emergence of vocants in infant utterances

This preliminary study was designed to determine if the point vowels /ɑ/, /i/ and /u/ emerge in a particular order and within specific age ranges in the productions of infants. Vowel‐like sounds (vocants) were selected randomly within certain general criteria from the cooing, expansion, and babbling periods of vocal development in two normal female infants. The formant frequencies of these vocants were estimated, at several points, by inspecting the wideband spectrogram, a 32‐ms spectral section, an inverse LPC spectrum, and the frequencies and bandwidths obtained by finding the roots of the denominator polynomial of the LPC model. The order of the LPC model was chosen adaptively to provide frequency resolution consistent with the fundamental frequency of voicing for each frame in order to minimize the interaction between harmonic and resonance locations. The results indicated (1) only modest changes in formant structure from the cooing to the expansion period and (2) a frequent lowering of the first formant and raising of the second in the babbling period, suggesting that an /i/‐like vocant does not emerge until the babbling period. Perceptual data for these vocants will be reported. [Work supported by NICHD grant HD 11970.]

Discriminant analysis on an imitation dialect

A data set consisting of phoneticians' limitations of a set of target vowels was LPC spectrum analyzed and quantized into 19 one-third-octave bins. These data were treated by discriminant analysis. Depending on the input data set, classification accuracy varied from 88.5% to 99.5%. Vowel categories are found to be arranged in discriminant function space much as they would be expected to appear on a phonetic vowel chart or a F1/F1 space except at the “front-back” dimension is relatively foreshortened. The results are interpreted as an analytic form of the dispersion hypothesis, according to which the vowels of a given language are maximally dispersed in vowel space [cf. J. Liljencrantz and B. Lindblom, “A numerical simulation of vowel quality systems,” Language 48, 839–862 (1972)]. [Work supported by NSF.]