Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Reconeixement de veu mitjançant xarxes neuronals

La interacció home-màquina per mitjà de la veu cobreix moltes àrees d’investigació. Es destaquen entre altres, el reconeixement de la parla, la síntesis i identificació de discurs, la verificació i identificació de locutor i l’activació per veu (ordres) de sistemes robòtics. Reconèixer la parla és natural i simple per a les persones, però és un treball complex per a les màquines, pel qual existeixen diverses metodologies i tècniques, entre elles les Xarxes Neuronals. L’objectiu d’aquest treball és desenvolupar una eina en Matlab per al reconeixement i identificació de paraules pronunciades per un locutor, entre un conjunt de paraules possibles, i amb una bona fiabilitat dins d’uns marges preestablerts. El sistema és independent del locutor que pronuncia la paraula, és a dir, aquest locutor no haurà intervingut en el procés d’entrenament del sistema. S’ha dissenyat una interfície que permet l’adquisició del senyal de veu i el seu processament mitjançant xarxes neuronals i altres tècniques. Adaptant una part de control al sistema, es podria utilitzar per donar ordres a un robot com l’Alfa6Uvic o qualsevol altre dispositiu.

Reconeixement de veu mitjançant xarxes neuronals

La interacció home-màquina per mitjà de la veu cobreix moltes àrees d’investigació. Es destaquen entre altres, el reconeixement de la parla, la síntesis i identificació de discurs, la verificació i identificació de locutor i l’activació per veu (ordres) de sistemes robòtics. Reconèixer la parla és natural i simple per a les persones, però és un treball complex per a les màquines, pel qual existeixen diverses metodologies i tècniques, entre elles les Xarxes Neuronals. L’objectiu d’aquest treball és desenvolupar una eina en Matlab per al reconeixement i identificació de paraules pronunciades per un locutor, entre un conjunt de paraules possibles, i amb una bona fiabilitat dins d’uns marges preestablerts. El sistema és independent del locutor que pronuncia la paraula, és a dir, aquest locutor no haurà intervingut en el procés d’entrenament del sistema. S’ha dissenyat una interfície que permet l’adquisició del senyal de veu i el seu processament mitjançant xarxes neuronals i altres tècniques. Adaptant una part de control al sistema, es podria utilitzar per donar ordres a un robot com l’Alfa6Uvic o qualsevol altre dispositiu.

L’effet de la familiarité sur l’identification des locuteurs : pour un perfectionnement de la parade vocale

La présente étude porte sur les effets de la familiarité dans l’identification d’individus en situation de parade vocale. La parade vocale est une technique inspirée d’une procédure paralégale d’identification visuelle d’individus. Elle consiste en la présentation de plusieurs voix avec des aspects acoustiques similaires définis selon des critères reconnus dans la littérature. L’objectif principal de la présente étude était de déterminer si la familiarité d’une voix dans une parade vocale peut donner un haut taux d’identification correcte (> 99 %) de locuteurs. Cette étude est la première à quantifier le critère de familiarité entre l’identificateur et une personne associée à « une voix-cible » selon quatre paramètres liés aux contacts (communications) entre les individus, soit la récence du contact (à quand remonte la dernière rencontre avec l’individu), la durée et la fréquence moyenne du contact et la période pendant laquelle avaient lieu les contacts. Trois différentes parades vocales ont été élaborées, chacune contenant 10 voix d’hommes incluant une voix-cible pouvant être très familière; ce degré de familiarité a été établi selon un questionnaire. Les participants (identificateurs, n = 44) ont été sélectionnés selon leur niveau de familiarité avec la voix-cible. Toutes les voix étaient celles de locuteurs natifs du franco-québécois et toutes avaient des fréquences fondamentales moyennes similaires à la voix-cible (à un semi-ton près). Aussi, chaque parade vocale contenait des énoncés variant en longueur selon un nombre donné de syllabes (1, 4, 10, 18 syll.). Les résultats démontrent qu’en contrôlant le degré de familiarité et avec un énoncé de 4 syllabes ou plus, on obtient un taux d’identification avec une probabilité exacte d’erreur de p < 1 x 10-12. Ces taux d’identification dépassent ceux obtenus actuellement avec des systèmes automatisés.

On the determination of epsilon during discriminative GMM training

Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.

Efficacy of educational interventions to reduce homophobia on the *college campus

Homophobic attitudes, irrational fears and negative attitudes against gay men and lesbians exist on the college campus (Lance, 2002; Rankin, 2003). Educators wishing to change these attitudes need to know what types of intervention would be effective. This investigation empirically assessed the degree of homophobia in a group of college students, and changes in the degree of homophobia following two levels of educational intervention that were rooted in educational theories and social contact theory. A 25-item scale developed by Hudson and Ricketts to measure the degree of negative attitudes toward gay men and lesbians was used in English classes at a southeastern university. This study examined the relationship between different demographic groups and the degree of change obtained as a result of the interventions. ^ Findings did not suggest that either interaction with gay men and lesbians in the form of a speaker panel or viewing a “coming out” episode of the Ellen show reduced homophobia to a significant extent. Results did demonstrate the Caribbeans and right wing authoritarians tend to be more homophobic. Post hoc analysis investigated factors that may have contaminated the interventions. Speaker Identification was a significant predictor of change in degree of homophobia. ^

Efficacy of Educational Interventions to Reduce Homophobia on the College Campus

Homophobic attitudes, irrational fears and negative attitudes against gay men and lesbians exist on the college campus (Lance, 2002; Rankin, 2003). Educators wishing to change these attitudes need to know what types of intervention would be effective. This investigation empirically assessed the degree of homophobia in a group of college students, and changes in the degree of homophobia following two levels of educational intervention that were rooted in educational theories and social contact theory. A 25-item scale developed by Hudson and Ricketts to measure the degree of negative attitudes toward gay men and lesbians was used in English classes at a southeastern university. This study examined the relationship between different demographic groups and the degree of change obtained as a result of the interventions. Findings did not suggest that either interaction with gay men and lesbians in the form of a speaker panel or viewing a “coming out” episode of the Ellen show reduced homophobia to a significant extent. Results did demonstrate the Caribbeans and right wing authoritarians tend to be more homophobic. Post hoc analysis investigated factors that may have contaminated the interventions. Speaker Identification was a significant predictor of change in degree of homophobia.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Perceptual compensation for reverberation in speech identification: effects of single-band, multiple-band and wideband noise contexts

Perceptual effects of room reverberation on a "sir" or "stir" test-word can be observed when the level of reverberation in the word is increased, while the reverberation in a surrounding 'context I utterance remains at a minimal level. The result is that listeners make more "sit" identifications. When the context's reverberation is also increased, to approach the level in the test word, extrinsic perceptual compensation is observed, so that the number of listeners' "sir" identifications reduces to a value similar to that found with minimal reverberation. Thus far, compensation effects have only been observed with speech or speech-like contexts in which the short-term spectrum changes as the speaker's articulators move. The results reported here show that some noise contexts with static short-term spectra can also give rise to compensation. From these experiments it would appear that compensation requires a context with a temporal envelope that fluctuates to some extent, so that parts of it resemble offsets. These findings are consistent with a rather general kind of perceptual compensation mechanism; one that is informed by the 'tails' that reverberation adds at offsets. Other results reported here show that narrow-band contexts do not bring about compensation, even when their temporal-envelopes are the same as those of the more effective wideband contexts. These results suggest that compensation is confined to the frequency range occupied by the context, and that in a wideband sound it might operate in a 'band by band' manner.

Perceptual compensation for effects of reverberation in speech identification

Listeners were asked to identify modified recordings of the words "sir" and "stir," which were spoken by an adult male British-English speaker. Steps along a continuum between the words were obtained by a pointwise interpolation of their temporal-envelopes. These test words were embedded in a longer "context" utterance, and played with different amounts of reverberation. Increasing only the test-word's reverberation shifts the listener's category boundary so that more "sir"-identifications are made. This effect reduces when the context's reverberation is also increased, indicating perceptual compensation that is informed by the context. Experiment I finds that compensation is more prominent in rapid speech, that it varies between rooms, that it is more prominent when the test-word's reverberation is high, and that it increases with the context's reverberation. Further experiments show that compensation persists when the room is switched between the context and the test word, when presentation is monaural, and when the context is reversed. However, compensation reduces when the context's reverberation pattern is reversed, as well as when noise-versions of the context are used. "Tails" that reverberation introduces at the ends of sounds and at spectral transitions may inform the compensation mechanism about the amount of reflected sound in the signal. (c) 2005 Acoustical Society of America.

Speech Signals Feature Extraction Model for a Speaker’s Gender and Age Identification System

Durante el proceso de producción de voz, los factores anatómicos, fisiológicos o psicosociales del individuo modifican los órganos resonadores, imprimiendo en la voz características particulares. Los sistemas ASR tratan de encontrar los matices característicos de una voz y asociarlos a un individuo o grupo. La edad y sexo de un hablante son factores intrínsecos que están presentes en la voz. Este trabajo intenta diferenciar esas características, aislarlas y usarlas para detectar el género y la edad de un hablante. Para dicho fin, se ha realizado el estudio y análisis de las características basadas en el pulso glótico y el tracto vocal, evitando usar técnicas clásicas (como pitch y sus derivados) debido a las restricciones propias de dichas técnicas. Los resultados finales de nuestro estudio alcanzan casi un 100% en reconocimiento de género mientras en la tarea de reconocimiento de edad el reconocimiento se encuentra alrededor del 80%. Parece ser que la voz queda afectada por el género del hablante y las hormonas, aunque no se aprecie en la audición. ABSTRACT Particular elements of the voice are printed during the speech production process and are related to anatomical and physiological factors of the phonatory system or psychosocial factors acquired by the speaker. ASR systems attempt to find those peculiar nuances of a voice and associate them to an individual or a group. Age and gender are inherent factors to the speaker which may be represented in voice. This work attempts to differentiate those characteristics, isolate them and use them to detect speaker’s gender and age. Features based on glottal pulse and vocal tract are studied and analyzed in order to achieve good results in both tasks. Classical methodologies (such as pitch and derivates) are avoided since the requirements of those techniques may be too restrictive. The final scores achieve almost 100% in gender recognition whereas in age recognition those scores are around 80%. Factors related to the gender and hormones seem to affect the voice although they are not audible.

Development of a genre-dependent TTS system with cross-speaker speaking-style transplantation

One of the biggest challenges in speech synthesis is the production of contextually-appropriate naturally sounding synthetic voices. This means that a Text-To-Speech system must be able to analyze a text beyond the sentence limits in order to select, or even modulate, the speaking style according to a broader context. Our current architecture is based on a two-step approach: text genre identification and speaking style synthesis according to the detected discourse genre. For the final implementation, a set of four genres and their corresponding speaking styles were considered: broadcast news, live sport commentaries, interviews and political speeches. In the final TTS evaluation, the four speaking styles were transplanted to the neutral voices of other speakers not included in the training database. When the transplanted styles were compared to the neutral voices, transplantation was significantly preferred and the similarity to the target speaker was as high as 78%.

Mucopolysaccharidosis Type Ii: Identification Of 30 Novel Mutations Among Latin American Patients.

In this study, 103 unrelated South-American patients with mucopolysaccharidosis type II (MPS II) were investigated aiming at the identification of iduronate-2-sulfatase (IDS) disease causing mutations and the possibility of some insights on the genotype-phenotype correlation The strategy used for genotyping involved the identification of the previously reported inversion/disruption of the IDS gene by PCR and screening for other mutations by PCR/SSCP. The exons with altered mobility on SSCP were sequenced, as well as all the exons of patients with no SSCP alteration. By using this strategy, we were able to find the pathogenic mutation in all patients. Alterations such as inversion/disruption and partial/total deletions of the IDS gene were found in 20/103 (19%) patients. Small insertions/deletions/indels (<22 bp) and point mutations were identified in 83/103 (88%) patients, including 30 novel mutations; except for a higher frequency of small duplications in relation to small deletions, the frequencies of major and minor alterations found in our sample are in accordance with those described in the literature.

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.