Tonsillar surface swab bacterial culture results differ from those of the tonsillar core in recurrent tonsillitis

Objectives/Hypothesis We aimed to determine whether there was a difference between core and surface bacteriology of Finnish adults with recurrent or chronic tonsillitis to understand whether a surface swab is worthwhile and which bacteria are involved. Study Design Case series. Methods Uninflamed tonsillar surface swabs and core biopsies were taken prior to and during surgery, respectively, in 103 patients aged 16 to 66 years undergoing tonsillectomy for recurrent or chronic tonsillitis. The McNemar test was used to determine differences between the surface and core in the most prevalent bacterial species. Results Twenty-seven bacterial species were isolated in addition to normal flora and were more commonly found in the core (1.11 surface and 4.75 core bacteria isolated per patient). Viridans group streptococci were the most commonly detected bacteria, found in 88% of the patients, mainly in the core. The bacteria in general were mainly isolated from the core. Of the 10 most prevalent bacteria, only group C beta-hemolytic streptococci showed no difference between detection from core and surface swabs. Other bacteria found mainly in the core include Prevotella melaninogenica, Staphylococcus aureus, and fusobacteria. Conclusions There is discord between the surface and core bacteria. A different population of bacteria exists in the core, especially anaerobic bacteria, suggesting that a core sample may be useful in evaluating recurrent and chronic tonsillitis. Level of Evidence 4 Laryngoscope, 2019Peer reviewe

Prediction of voice aperiodicity based on spectral representations in HMM speech synthesis

Abstract In hidden Markov model-based speech synthesis, speech is typically parameterized using source-filter decomposition. A widely used analysis/synthesis framework, STRAIGHT, decomposes the speech waveform into a framewise spectral envelope and a mixed mode excitation signal. Inclusion of an aperiodicity measure in the model enables synthesis also for signals that are not purely voiced or unvoiced. In the traditional approach employing hidden Markov modeling and decision tree-based clustering, the connection between speech spectrum and aperiodicities is not taken into account. In this paper, we take advantage of this dependency and predict voice aperiodicities afterwards based on synthetic spectral representations. The evaluations carried out for English data confirm that the proposed approach is able to provide prediction accuracy that is comparable to the traditional approach

Parameterization of Vocal Fry in HMM-Based Speech Synthesis

HMM-based speech synthesis offers a way to generate speech with different voice qualities. However, sometimes databases contain certain inherent voice qualities that need to be parametrized properly. One example of this is vocal fry typically occurring at the end of utterances. A popular mixed excitation vocoder for HMM-based speech synthesis is STRAIGHT. The standard STRAIGHT is optimized for modal voices and may not produce high quality with other voice types. Fortunately, due to the flexibility of STRAIGHT, different F0 and aperiodicity measures can be used in the synthesis without any inherent degradations in speech quality. We have replaced the STRAIGHT excitation with a representation based on a robust F0 measure and a carefully determined two-band voicing. According to our analysis-synthesis experiments, the new parameterization can improve the speech quality. In HMM-based speech synthesis, the quality is significantly improved especially due to the better modeling of vocal fry. Index Terms: speech synthesis, hidden Markov models, vocal fry, mixed excitation, STRAIGH