Objective: To evaluate outcome of two types of tonsil surgery (tonsillectomy+adenoidectomy or tonsillotomy +adenoidectomy) on vocal function perceptually and acoustically. Study Design: Sixty-seven children, aged 50-65 months, on waiting list for tonsil surgery were randomized to tonsillectomy (n=33) or tonsillotomy (n=34). Fifty-seven age and gender matched healthy pre-school children were controls. Twenty-eight of them, aged 48-59 months, served as control group before surgery, and 29, aged 60-71 months, after surgery Methods: Before surgery and six months postoperatively, the children were recorded producing three sustained vowels (/A, u, i/) and 14 words. The control groups were recorded only once. Three trained speech and language pathologists performed the perceptual analysis using Visual Analogue Scales (VAS) for eight voice quality parameters. Acoustic analysis from sustained vowels included average fundamental frequency, jitter percent, shimmer percent, noise-to-harmonic ratio and the centre frequencies of formants 1-3 Results: Before surgery the children were rated to have more hyponasality and compressed/throaty voice (p<0,05) and  lower mean pitch (p<0,01) in comparison to the control group. They also had higher perturbation measures and lower frequencies of the second and third formant. After surgery there were no differences perceptually. Perturbation measures decreased but were still higher compared to the control group’s, p<0, 05. Differences in formant frequencies for /i/ and /u/ remained. No differences were found between the two surgical methods. Conclusion: Voice quality is affected perceptually and acoustically by adenotonsillar hypertrophy. After surgery the voice is perceptually normalized but acoustic differences remain. Outcome was equal for both surgical methods.

The taxonomic status of Mirafra cantillans and M. javanica has undergone revision severaltimes: sometimes considered a single species, but most often considered two separate species.Recent mitochondrial (Alström et al. 2013) and multilocus (Alström et al. 2023) studies havecontributed to this dynamic, with the mitochondrial data suggesting that there is only onespecies, while the genomic data is more indicative of two species. Despite this, vocalizations,a known tool for identifying avian species and an important source of data in taxonomicstudies, have not yet been analyzed for this species complex. This study analyzed recordingsof vocalizations of M. cantillans and M. javanica (here treated as two species) to provide newinsight into their taxonomy. Based on over 150 recordings from across the range (westernAfrica to eastern Australia), I used a combination of numerical measurements, auditory, andvisual data to evaluate their taxonomy. Overlap and consistencies between the patterns of thesongs was found throughout the entire range of the complex, with the most vocally distinctgeographical population identified being from India, though there was significant overlapbetween all populations. Mimicry, continuous songs, and block patterning were found to bepresent throughout the majority of the populations from different geographical regions. Threegeographically separate song types were identified (Africa to Arabia, India, and SoutheastAsia to Australia).

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2017-09-19T15:36:01Z No. of bitstreams: 1 Dissertacao_SergioEspinola_CEEI_UFCG.pdf: 59559230 bytes, checksum: 045a4738e365ab656e17da8b2185cb9b (MD5) / Made available in DSpace on 2017-09-19T15:36:01Z (GMT). No. of bitstreams: 1 Dissertacao_SergioEspinola_CEEI_UFCG.pdf: 59559230 bytes, checksum: 045a4738e365ab656e17da8b2185cb9b (MD5) Previous issue date: 2014-03-12 / Estima-se que um terço da força de trabalho humana dependa da voz para realização de seus ofícios. Procedimentos médicos avaliam a qualidade vocal do indivíduo sendo os mais usados aqueles baseados na escuta da voz (subjetivo) ou na inspeção das dobras (ou pregas) vocais por exames sofisticados (objetivos, porém invasivos e caros). A análise acústica da voz busca extrair medidas robustas para descrever vários fenômenos associados à produção da fala ou características intrínsecas do ser humano como frequência fundamental, timbre, etc. O presente estudo consiste na caracterização de um modelo de processamento digital de Voz para apoio ao diagnóstico no contexto da construção de sistemas de identificação automatizados de patologias da fala. Para análise da técnica proposta foi utilizada uma base de dados (base KAY) que foi estruturada por especialistas num arranjo de seis grupos de Patologias. A esse, acrescentado também um de vozes “Normal”. Assim, 182 vozes foram escolhidas, as quais dispunham de um catálogo indexado de cerca de 33 descritores, para cada voz, calculados da elocução da vogal \a\ sustentada. Ao selecionar combinações desses descritores – como perturbações em frequência (jitter), em amplitude (shimmer) etc, este estudo encontrou evidências estatísticas e mostrou ser possível: a) Separar vozes normais das patológicas – esperado, b) Separar patologias específicas (Paralisia, Edema de Reinke, Nódulos) com acurácia de 100% (para a grande maioria dessas combinações) e cerca de 92% (para Nódulos contra Reinke); c) Discriminá-las por meio de classificadores (redes neurais artificiais e máquina de vetores de suporte) e reduzir a dimensionalidade e complexidade (quantidade de dados) via técnica de análise de componentes principais (ACP) sobre esses descritores para a separação intra patologias; e d) Testes estatísticos com os grupos locais confirmaram também limiares de indícios de Anormalidade presentes na literatura. A utilização de menor quantidade de descritores – obtida pós ACP (compressão) – mostrou-se também eficiente (mesmas taxas de acurácia). / It is estimated one-third of the work force relies on the use the voice in their jobs. The clinical diagnostic may be performed on voice listening by a specialist (subjective perspective) or through invasive and often not cheaper exams to check vocal structures. The area of Voice Acoustic analyses aims to extract robust measurements to describe several phenomena associated with voice production, or human being particular characteristics like fundamental frequency, timbre, etc. This study consisted of a model characterizing the digital voice processing for support in building automatic systems for the identification of disorders of speech (to aid diagnosis of pathologies). To support this investigation and proposed model, a commercial voice database (KAY base) was used with the endorsement from medical specialists. Derived acoustic analyses of those speech samples data records were presented to professionals for classification and six “severities groups” case-studied were built. After these analyses, one Normal group was added and, at the end, 182 voices have been selected. Their refined audio database contain, among other things, an indexed list of vocal descriptors calculated on the presence of the utterance of the vowel \a\ sustained speech. Statistical evidences were found: a) Difference between pathological groups vocal descriptors to normal (expected); b) It was achieved 100% from true positive, most cases, among Paralysis, Reinke's Edema and Nodules separations; c) from few cases, there were detected minor distinctions: Paralysis, Reinke's Edema, Nodules and Edema (pair comparison) with disordered groups; c) Among Machine Learning Algorithms (artificial neural networks "RN" and support vector machine "SVM"), the technique of Principal Components Analyses (PCA) and main statistics performed, it was found facts to help to structure some automated recognition systems. These Supervised learning methods showed that it could be possible to generate classification predictions (disordered presence) for the response to new data; and d) Inner tests also confirmed literature established reference thresholds. Hence considering suitable combinations of descriptors with two machine learning classifiers, as showed, is sufficient suitable and worthy.

This study presents detailed phonetic and acoustic analyses of the speech characteristics of two new cases of Foreign Accent Syndrome (FAS). Participants include a 48-year-old female who began speaking with an "Eastern European" accent following a traumatic brain injury, and a 45-year-old male who presented with a "British" accent following a subcortical cerebral vascular accident (CVA). Identical samples of the participants' pre- and post-morbid speech were obtained, thus affording a new level of control in the study of Foreign Accent Syndrome. The speech tasks consisted of oral readings of the Grandfather Passage and 18 real words comprised of the stop consonants /p/, /t/, /k/, /b/, /d/, /g/ combined with the peripheral vowels /i/, /a/ and /u/ and ending in a voiceless stop. Computer-based acoustic measures included: 1) voice onset time (VOT), 2) vowel durations, 3) whole word durations, 4) first, second and third formant frequencies, and 5) fundamental frequency. Formant frequencies were measured at three points in the vowel duration: a) 20%, b) 50%, and c) 80% to assess differences in vowel 'onglides' and 'offglides'. The phonetic analysis provided perceptual identification of the major phonetic features associated with the foreign quality of participant's FAS speech, while acoustic measures allowed precise quantification of these features. Results indicated evidence of backing of consonant and vowel productions for both participants. The implications for future research and clinical applications are also considered.