Modeling of Spectra and Temporal Trajectories in Speech Processing

This work investigates the application of spectral and temporal speech processing algorithms developed for feature extraction in Automatic Speech Recognition (ASR) and for very low bit-rate speech coding. In the first part of the thesis, various spectral processing feature extraction techniques are investigated for robust parameterization of speech. We are especially focused on all-pole modeling based techniques that use, as the major processing block, autoregressive model to suppress speaker-dependent details in the auditory spectrum. Such techniques that use the model spectrum are advantageous as opposed to directly using signal auditory spectrum. The model spectrum can be represented by various types of parameters that have different properties (decorrelation property, quantization, robustness on additive and convolutive noise,...). We show that even though cepstrum-based speech features are mostly used for ASR, the best recognition performances are achieved using decorrelated and normalized Line Spectral Frequencies (LSFs). Furthermore, frequency selective and discrete all-pole modeling approaches are studied and their efficient properties on final speech features are presented. We take also into account feature normalization techniques and mention their influence on extracted speech features. The most significant experimental results are achieved on well-known SpeechDat-Ca

Racionalizace informačního systému obchodní společnosti Soft-Tronik, s.r.o.

Import 20/04/2006Prezenční výpůjčkaVŠB - Technická univerzita Ostrava. Ekonomická fakulta. Katedra (155) informatiky v ekonomic

Multimodal Phoneme Recognition of Meeting Data

Abstract. This paper describes experiments in automatic recognition of context-independent phoneme strings from meeting data using audiovisual features. Visual features are known to improve accuracy and noise robustness of automatic speech recognizers. However, many problems appear when not “visually clean ” data is provided, such as data without limited variation in the speaker’s frontal pose, lighting conditions, background, etc. The goal of this work was to test whether visual information can be helpful for recognition of phonemes using neural nets. While the audio part is fixed and uses standard Mel filter-bank energies, different features describing the video were tested: average brightness, DCT coefficients extracted from region-of-interest (ROI), optical flow analysis and lip-position features. The recognition was evaluated on a sub-set of IDIAP meeting room data. We have seen small improvement when compared to purely audio-recognition, but further work needs to be done especially concerning the determination of reliability of video features.

VISUAL FEATURES FOR MULTIMODAL SPEECH RECOGNITION

This paper demonstrates the use of visual parameters extracted from video for automatic recognition of phoneme strings. Encouraged by previous works utilizing ”visually clean” data we investigate their efficiency in non-ideal conditions which are introduced by meeting audio-visual data employed in our experiments.

PITCH DETECTOR IN SPEECH PROCESSING ABSTRACT

The paper presents a novel method for detection of pitch in speech processing. The work focuses on a time domain algorithm for segmenting voiced speech that uses similarity of adjacent segments. The experimental results while testing this detector are presented and compared to OGIvox speech database. 1 ÚVOD Základním tónem rozumíme základní kmitočet (pitch) na kterém kmitají hlasivky. Spolu s formantovými frekvencemi patˇrí mezi základní fonetické charakteristiky ˇrečového signálu. Využívá se zejména v syntetizátorech a kodérech ˇreči. Existují dvě skupiny metod pracující v časové nebo ve frekvenční oblasti. V časové oblasti se využívá podobnosti ˇrečových úsek ˚ u a ve frekven ční napˇr. vlastností lichých harmonických. Dále bude věnována pozornost detektoru pracujícím v časové oblasti. 2 SEGMENTACE V ČASOVÉ OBLASTI Cílem segmentace je rozdělení ˇrečového signálu na takové části, z nichž délka každé části pˇrímo odpovídá periodě základního tónu ve zkoumaném úseku. Mějme znělý ˇrečový signál a v něm dva sousedící segmenty U1 a U2 začínající v místě, kde signál protíná časovou osu pˇri vzestupu ze záporných hodnot do kladných. Nejjednodušším zp ˚ usobem, jak ohodnotit podobnost segment ˚ u, je ur čit energii rozdílového signálu mezi odpovídajícími si vzorky podle (1). d(U1,U2) = min(n1,n2) n=1 (x1[n] − x2[n]) 2, (1) kde Ui = (xi[1],xi[2],...,xi[ni]) pro i = 1,2 jsou segmenty signálu a ni pro i = 1,2 jsou délky segment ˚ u. Nyní hledáme takovou posloupnost dělících bod ˚ u pro kterou je sou čet dílčích vzdáleností mezi sousedícími segmenty minimální, pˇričemž posloupnost musí začínat (končit) ve vzdálenosti dmin od začátku (konce) signálu a dále největší možná délka segment ˚ u je dmax. Hodnoty udává (2). dmin = Fs, dmax

Compositional properties and bioactive potential of waste material from shrimp cooking juice

A functional concentrate rich in proteins and lipids was obtained from an industrial shrimp cooking juice by using a centrifugal separator, and it was characterized in terms of chemical composition parameters and functional or biological activity (antioxidant and ACE-inhibitory capacities). The concentrate presented 116g/kg protein, 135g/kg crude fat and ash content less than 10g/kg, with predominance of Na ions, followed by K, Ca, Mg, Cu, Fe, Zn and Mn. A relative abundance of glucose, glycerol, polyalcohols, acetate and phosphate was found. The antioxidant (as determined by ABTS, FRAP, chelating and photoluminescence assays) and ACE-inhibitory capacities of the material recovered from the shrimp cooking juice were strongly related to the presence of small peptides (1355-502Da), with a clear predominance of Gly, Pro, Glu, Asp and Arg. Other antioxidants, such as free astaxanthin (cis and trans isomers) and derived esters, were also detected. © 2013 Elsevier Ltd.This research was financed by the Spanish Ministry of Economy and Competitiveness through project AGL2011-27607.Peer Reviewe