Surface Electromyography–Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech

Purpose This study aimed to evaluate a novel communication system designed to translate surface electromyographic (sEMG) signals from articulatory muscles into speech using a personalized, digital voice. The system was evaluated for word recognition, prosodic classification, and listener perception of synthesized speech. Method sEMG signals were recorded from the face and neck as speakers with ( n = 4) and without ( n = 4) laryngectomy subvocally recited (silently mouthed) a speech corpus comprising 750 phrases (150 phrases with variable phrase-level stress). Corpus tokens were then translated into speech via personalized voice synthesis ( n = 8 synthetic voices) and compared against phrases produced by each speaker when using their typical mode of communication ( n = 4 natural voices, n = 4 electrolaryngeal [EL] voices). Naïve listeners ( n = 12) evaluated synthetic, natural, and EL speech for acceptability and intelligibility in a visual sort-and-rate task, as well as phrasal stress discriminability via a classification mechanism. Results Recorded sEMG signals were processed to translate sEMG muscle activity into lexical content and categorize variations in phrase-level stress, achieving a mean accuracy of 96.3% ( SD = 3.10%) and 91.2% ( SD = 4.46%), respectively. Synthetic speech was significantly higher in acceptability and intelligibility than EL speech, also leading to greater phrasal stress classification accuracy, whereas natural speech was rated as the most acceptable and intelligible, with the greatest phrasal stress classification accuracy. Conclusion This proof-of-concept study establishes the feasibility of using subvocal sEMG-based alternative communication not only for lexical recognition but also for prosodic communication in healthy individuals, as well as those living with vocal impairments and residual articulatory function. Supplemental Material https://doi.org/10.23641/asha.14558481

Metabolism of Non-growing Cells and Their Application in Biotransformation

Growing cells is the typical mode of operation in many aspects of biotechnology and metabolic engineering. This comes about due to cell growth processes creating a driving force that pull metabolic flux along different metabolic pathways, that indirectly help move substrate to product. But, there is an alternative mode of operation that uses resting (non-growing) cells to achieve similar or even higher productivities. In general, resting cells are provided with carbon substrates for biocatalytic reactions but starved of nitrogen or phosphorus. Such resting cells have been usefully employed in many forms of biocatalysis and biotransformation, with or without cofactor regeneration. However, much remains unknown about the transcriptome and metabolome of resting cells in biotransformation settings. This short writeup provides the backdrop of resting cells in biocatalysis, documents their use in biotransformation with application examples, and identifies research gaps that could be filled with contemporary RNA-seq and mass spectrometry proteomics technology. Overall, utility of resting cells in biocatalysis and the extant knowledge gap in their fundamental physiology are highlighted in this resource.

Sociopolitical Attitudes Through the Lens of Behavioral Genetics: Contributions from Dr Nicholas Martin

Professor Nicholas (Nick) Martin spearheaded initial investigations into the genetic basis of political attitudes and behaviors, demonstrating that behaviors that are perceived as socially constructed could have a biological basis. As he showed, the typical mode of inheritance for political attitudes consists of approximately equal proportions of variance from additive genetic, shared environmental and unique environmental sources. This differs from other psychological variables, such as personality traits, which tend to be characterized by genetic and unique environmental sources of variation. By treating political attitudes as a model phenotype, Nick Martin was able to leverage the unique pattern of observed intergenerational transmission for political attitudes to reexamine the quintessential assumptions of the classical twin model. Specifically, by creatively leveraging the nuances of the genetic architecture of political attitudes, he was able to demonstrate the robustness of the equal environments assumption and suggest corrections to account for assortative mating. These advances have had a substantial impact on both the fields of political science, as well as behavioral and quantitative genetics.

Scots law: a system in search of a family?

The concept of legal families is familiar to most comparativists and although miscegenation is an increasingly common feature in a global community, arguably an understanding of family origins may help to anticipate differences of approach, ideology, attitudes to law and diverging normative values. Classification into families, despite various criticisms and disagreements as to which families there are or how they should be distinguished, provides a useful tool for the comparativists and those seeking, reform, unification or harmonisation.The Scottish legal system, however, is one that tends to elude classification. Even where “mixed” or “hybrid” legal systems are recognised, that of Scotland may be omitted or distinguished from those of, for example, Greece, South Africa, Israel or the Seychelles.This begs the question, what is a legal system and how is it distinguished? This paper examines the Scottish legal system, taking as its starting point a focus on juristic style as the key distinguishing feature of a legal system and looking at the key elements that eminent comparativists Zweigert and Kötz suggest shape this. These are: the historical background and development; its typical mode of thought; its distinctive institutions; the types of legal sources it acknowledges; and its ideology. Looking particularly at the academic debates that have arisen in Scotland concerning the nature and identity of Scots law, the paper goes on toconsider whether the claim to a distinct legal system is anything more than a manifestation of the fact that “each political society in the world has its own law”,1 and that in fact the time has come to abandon the notion of families.

Youth and Women Lead

Diane Nash, Bob Moses, and The Student Nonviolent Coordinating Committee (SNCC) routed an oppressive system that had existed for nearly a century. In just five years, between 1960 and 1965, young activists—most Black, some not—dismantled large parts of legalized segregation, a system widely known as Jim Crow. They set up voting rights, community organizing, and nonviolent direct action in the very places in which segregation was most deeply rooted—Mississippi, Alabama, Tennessee, and Georgia. Ella Baker, possibly the greatest champion of American democratic politics that no one outside of certain circles has ever heard about—was a lodestar for SNCC’s group-centered leadership. Baker resisted the typical mode of individual heroics. Her legacy not only pervades the story of SNCC but also becomes visible in many of the movements that followed the civil rights/Black Power era.

The emergence of multiple populations in radiation hydrodynamics simulations of cluster formation

We present a new approach to understanding star-to-star helium abundance variations within globular clusters. We begin with detailed radiation hydrodynamics simulations of cluster formation within giant molecular clouds, and investigate the conditions under which multiple populations could be created. Chemical enrichment occurs dynamically as the cluster is assembled. We test two extreme mechanisms for injection of enriched gas within the clusters, and find that realistic multiple populations can be formed in both mechanisms. The stochastic cluster formation histories are dictated by the inherent randomness of the timing and location of the formation of small clusters, which rapidly merge to build up the larger cluster, in combination with continual accretion of gas from the cloud. These cluster formation histories naturally produce a diversity of abundance patterns across the massive cluster population. We conclude that multiple populations are a natural outcome of the typical mode of star cluster formation.

Flutter Test Data Processing Based on Improved Hilbert-Huang Transform

Flutter tests are conducted primarily for the purpose of modal parameter estimation and flutter boundary prediction, the accuracy of which is severely affected by the acquired data quality, structural modal density, and nonstationary conditions. An improved Hilbert-Huang Transform (HHT) algorithm is presented in this paper which mitigates the typical mode mixing effect via modulation. The algorithm is validated by theory, by numerical simulation, and per actual flight flutter test data. The results show that the proposed method could extract the flutter model parameters and predict the flutter speed more accurately, which is feasible for the current flutter test data processing.

Numerical Analysis on Phonon Localization of Vacancy Type Disordered Graphene

The phonon properties of hydrogen passivated graphene with vacancy defects are studied using the forced vibrational method. The phonon density of states (PDOSs), typical mode patterns and localization length are calculated over a broad range of vacancies. We find that phonon properties of graphene strongly depend on the system size. We observe a broadening and softening of the PDOS peaks with the increase of vacancy concentrations. We find an increasing C – H stretching mode with the increase of defect density. Our numerical experiments reveal that the typical mode pattern for the K point in-plane TO (iTO) modes phonon show the spatial localized vibrations persuaded by vacancies, which are in conceptually good agreement with the large D band peak of the Raman spectra comes from the imperfections of crystal. For the K point iTO mode phonons, a typical localization length is on the order ≈ 5 nm for vacancy-type defects at high concentrations of 30% is observed. The localization effects manifest themselves in the projected temperature behavior of the constant-volume specific heat capacity of pristine and disordered graphene samples.