Evaluating speech synthesis intelligibility using Amazon Mechanical Turk

Microtask platforms such as Amazon Mechanical Turk (AMT) are increasingly used to create speech and language resources. AMT in particular allows researchers to quickly recruit a large number of fairly demographically diverse participants. In this study, we investigated whether AMT can be used for comparing the intelligibility of speech synthesis systems. We conducted two experiments in the lab and via AMT, one comparing US English diphone to US English speaker-adaptive HTS synthesis and one comparing UK English unit selection to UK English speaker-dependent HTS synthesis. While AMT word error rates were worse than lab error rates, AMT results were more sensitive to relative differences between systems. This is mainly due to the larger number of listeners. Boxplots and multilevel modelling allowed us to identify listeners who performed particularly badly, while thresholding was sufficient to eliminate rogue workers. We conclude that AMT is a viable platform for synthetic speech intelligibility comparisons

Twitter has a Binary Privacy Setting, are Users Aware of How It Works?

Twitter accounts are public by default, but Twitter gives the option to create protected accounts, where only approved followers can see their tweets. The publicly visible information changes based on the account type and the visibility of tweets also depends solely on the poster's account type which can cause unintended disclosures especially when users interact. We surveyed 336 Twitter users to understand users' awareness of account information visibility, as well as the tweet visibility when users interact. We find that our participants are aware of the visibility of their profile information and individual tweets. However, the visibility of followed topics, lists, and interactions with protected accounts is confusing. Only 31% of the participants were aware that a reply by a public account to a protected account's tweet would be publicly visible. Surprisingly, having a protected account does not result in a better understanding of the account information or tweet visibility.Comment: Proceeding of the 2023 ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW'23

The effects of lifestyle and diet on gut microbiota composition, inflammation and muscle performance in our aging society

Living longer is associated with an increased risk of chronic diseases, including impairments of the musculoskeletal and immune system as well as metabolic disorders and certain cancers, each of which can negatively affect the relationship between host and microbiota up to the occurrence of dysbiosis. On the other hand, lifestyle factors, including regular physical exercise and a healthy diet, can affect skeletal muscle and immune aging positively at all ages. Accordingly, health benefits could partly depend on the effect of such interventions that influence the biodiversity and functionality of intestinal microbiota. In the present review, we first discuss the physiological effects of aging on the gut microbiota, immune system, and skeletal muscle. Secondly, we describe human epidemiological evidence about the associations between physical activity and fitness and the gut microbiota composition in older adults. The third part highlights the relevance and restorative mechanisms of immune protection through physical activity and specific exercise interventions during aging. Fourth, we present important research findings on the effects of exercise and protein as well as other nutrients on skeletal muscle performance in older adults. Finally, we provide nutritional recommendations to prevent malnutrition and support healthy active aging with a focus on gut microbiota. Key nutrition‐related concerns include the need for adequate energy and protein intake for preventing low muscle mass and a higher demand for specific nutrients (e.g., dietary fiber, polyphenols and polyunsaturated fatty acids) that can modify the composition, diversity, and metabolic capacity of the gut microbiota, and may thus provide a practical means of enhancing gut and systemic immune function

The miscarriage circle of care:towards leveraging online spaces for social support

BACKGROUND: Lack of social support during and after miscarriage can greatly affect mental wellbeing. With miscarriages being a common experience, there remains a discrepancy in the social support received after a pregnancy is lost. METHOD: 42 people who had experienced at least one miscarriage took part in an Asynchronous Remote Community (ARC) study. The study involved 16 activities (discussions, creative tasks, and surveys) in two closed, secret Facebook groups over eight weeks. Descriptive statistics were used to analyse quantitative data, and content analysis was used for qualitative data. RESULTS: There were two main miscarriage care networks, formal (health care providers) and informal (friends, family, work colleagues). The formal care network was the most trusted informational support source, while the informal care network was the main source of tangible support. However, often, participants’ care networks were unable to provide sufficient informational, emotional, esteem, and network support. Peers who also had experienced miscarriage played a crucial role in addressing these gaps in social support. Technology use varied greatly, with smartphone use as the only common denominator. While there was a range of online support sources, participants tended to focus on only a few, and there was no single common preferred source. DISCUSSION: We propose a Miscarriage Circle of Care Model (MCCM), with peer advisors playing a central role in improving communication channels and social support provision. We show how the MCCM can be used to identify gaps in service provision and opportunities where technology can be leveraged to fill those gaps