Estimating underlying articulatory targets of Thai vowels by using deep learning based on generating synthetic samples from a 3D vocal tract model and data augmentation

Representation learning is one of the fundamental issues in modeling articulatory-based speech synthesis using target-driven models. This paper proposes a computational strategy for learning underlying articulatory targets from a 3D articulatory speech synthesis model using a bi-directional long short-term memory recurrent neural network based on a small set of representative seed samples. From a seeding set, a larger training set was generated that provided richer contextual variations for the model to learn. The deep learning model for acoustic-to-target mapping was then trained to model the inverse relation of the articulation process. This method allows the trained model to map the given acoustic data onto the articulatory target parameters which can then be used to identify the distribution based on linguistic contexts. The model was evaluated based on its effectiveness in mapping acoustics to articulation, and the perceptual accuracy of speech reproduced from the estimated articulation. The results indicate that the model can accurately imitate speech with a high degree of phonemic precision

Model-based exploration of linking between vowel articulatory space and acoustic space

While the acoustic vowel space has been extensively studied in previous research, little is known about the high-dimensional articulatory space of vowels. The articulatory imaging techniques are limited to tracking only a few key articulators, leaving the rest of the articulators unmonitored. In the present study, we attempted to develop a detailed articulatory space obtained by training a 3D articulatory synthesizer to learn eleven British English vowels. An analysis-by-synthesis strategy was used to acoustically optimize vocal tract parameters that represent twenty articulatory dimensions. The results show that tongue height and retraction, larynx location and lip roundness are the most perceptually distinctive articulatory dimensions. Yet, even for these dimensions, there is a fair amount of articulatory overlap between vowels, unlike the fine-grained acoustic space. This method opens up the possibility of using modelling to investigate the link between speech production and perception

Modell einer Frauenstimme für die artikulatorische Sprachsynthese mit VocalTractLab Studientexte zur Sprachkommunikation

Für das artikulatorische Sprachsynthesesystem VocalTractLab, das inder veröffentlichten Version auf dem geometrischen Modell eines männlichen Vokaltrakts basiert, wird das Modell für eine Frauenstimme vorgestellt. Anhand von MRT-Aufnahmen, Kieferabdrücken und Sprachaufnahmen einer ausgebildeten Sprecherinwurden die anatomischen Parameter für den weiblichen Vokaltrakt bestimmt und dieZielformen der Einzellaute sowie der glottalen Gesten angepasst. Die Sprachsynthese direkt aus Text oder einer phonetischen Transkription erfolgt mit VocalTractLab derzeit noch nicht automatisch. Die Schritte zur Erstellung von gestischen Partiturenwerden beschrieben und die Ergebnisse einer ersten Hörerbefragung zur Qualität dersynthetischen Frauenstimme präsentiert

Evoc-Learn - High quality simulation of early vocal learning

Evoc-Learn is a system for simulating early vocal learning of spoken language in ways that can overcome some of the major bottlenecks in vocal learning. The system consists of VocalTractLab, a geometrical three-dimensional vocal tract model for simulating aeroacoustics and articulatory dynamics, a coarticulation model for controlling the temporal dynamics of articulation, and a sensory feedback system for guiding the learning process. We will demonstrate each component of Evoc-Learn and show how they work together to simulate the learning of highly intelligible speech

Influence of the substrate-induced strain and irradiation disorder on the Peierls transition in TTF-TCNQ microdomains

The influence of the combined effects of substrate-induced strain, finite size and electron irradiation-induced defects have been studied on individual micron-sized domains of the organic charge transfer compound tetrathiafulvalene-tetracyanoquinodimethane (TTF-TCNQ) by temperature-dependent conductivity and current-voltage measurements. The individual domains have been isolated by focused ion beam etching and electrically contacted by focused ion and electron beam induced deposition of metallic contacts. The temperature-dependent conductivity follows a variable range hopping behavior which shows a crossover of the exponent as the Peierls transition is approached. The low temperature behavior is analyzed within the segmented rod model of Fogler, Teber and Shklowskii, as originally developed for a charge-ordered quasi one-dimensional electron crystal. The results are compared with data obtained on as-grown and electron irradiated epitaxial TTF-TCNQ thin films of the two-domain type

Ligand-induced type II interleukin-4 receptor dimers are sustained by rapid re-association within plasma membrane microcompartments

Biological and Soft Matter Physic

Direct observation of active material concentration gradients and crystallinity breakdown in LiFePO4 electrodes during charge/discharge cycling of lithium batteries

The phase changes that occur during discharge of an electrode comprised of LiFePO4, carbon, and PTFE binder have been studied in lithium half cells by using X-ray diffraction measurements in reflection geometry. Differences in the state of charge between the front and the back of LiFePO4 electrodes have been visualized. By modifying the X-ray incident angle the depth of penetration of the X-ray beam into the electrode was altered, allowing for the examination of any concentration gradients that were present within the electrode. At high rates of discharge the electrode side facing the current collector underwent limited lithium insertion while the electrode as a whole underwent greater than 50% of discharge. This behavior is consistent with depletion at high rate of the lithium content of the electrolyte contained in the electrode pores. Increases in the diffraction peak widths indicated a breakdown of crystallinity within the active material during cycling even during the relatively short duration of these experiments, which can also be linked to cycling at high rate