Analyzing Speech Recognition for Individuals with Down Syndrome

With the increment of voice assistants, speech recognition technologies have been used to support natural language processing. However, there are limitations on how well the technologies perform depending on who the users are. They have been predominantly trained on “typical speech” patterns, leaving aside people with disabilities with unique speech patterns. More specifically, people with Down Syndrome are having trouble using speech recognition technology due to their differences in speech. To develop a more accessible voice assistant, this project aims to characterize the speech recognition from individuals with Down Syndrome. To accomplish this aim, we analyze the quality of transcripts generated by two popular algorithms used for speech recognition (IBM and Google) to see the differences of speech from neurotypicals and people with Down Syndrome. We analyzed 7 videos of interviews between a neurotypical interviewer and Down Syndrome participants. We computed the symmetric differences between auto generated subtitles(IBM and youtube) and subtitles that were provided by humans (ground true) as well as the word error rate in all sentences. We found that current speech recognition algorithms don’t recognize Down Syndrome speeches as well as speeches from neurotypicals. We are currently analyzing the specific type of error. By finding the speech patterns for people with disabilities, speech recognition technologies will be more inclusive, and truly help those who need voice assistants the most

Thai Voice-Controlled Analysis for Car Parking Assistance in System-on-Chip Architecture

This paper introduces an analysis of Thai speech recognition for controlled car parking assist in the system-on-chip architecture. The objective is to investigate the male and female voice command signals, including Thai and English words, issued by the native Thai users. Hardware and software co-design by the Xilinx VIVADO are designed on an ARM multicore processor and a reconfigurable system on a ZYBO board. The experiments for Thai and English word recognition are conducted by using the Mel-frequency cepstral coefficient approach and presented in the form of spectrograms. The comparison of a voice command via Bluetooth and a reference command stored on an SD card and the ZYBO embedded board on a miniature electric vehicle is verified with the Pearson’s correlation coefficient (PCC). The experimental results show the accuracies of the received Thai/English, male/female, and indoor/outdoor voice commands as compared with the reference voice commands in the noisy surroundings. Hence, our system can support Thai/English and male/female voice commands to perform a set of actions for maneuvering a car by the PCC

A Systematic Review of Ethical Concerns with Voice Assistants

Siri's introduction in 2011 marked the beginning of a wave of domestic voice assistant releases, and this technology has since become commonplace in consumer devices such as smartphones and TVs. But as their presence expands there have also been a range of ethical concerns identified around the use of voice assistants, such as the privacy implications of having devices that are always recording and the ways that these devices are integrated into the existing social order of the home. This has created a burgeoning area of research across a range of fields including computer science, social science, and psychology. This paper takes stock of the foundations and frontiers of this work through a systematic literature review of 117 papers on ethical concerns with voice assistants. In addition to analysis of nine specific areas of concern, the review measures the distribution of methods and participant demographics across the literature. We show how some concerns, such as privacy, are operationalized to a much greater extent than others like accessibility, and how study participants are overwhelmingly drawn from a small handful of Western nations. In so doing we hope to provide an outline of the rich tapestry of work around these concerns and highlight areas where current research efforts are lacking

The enchanted house:An analysis of the interaction of intelligent personal home assistants (IPHAs) with the private sphere and its legal protection

Abstract In less than five years, Alexa has become a familiar presence in many households, and even those who do not own one have stumbled into it, be it at a friend’s house or in the news. Amazon Alexa and its friend Google Assistant represent an evolution of IoT: they have an advanced ‘intelligence’ based on Cloud computing and Machine Learning; they collect data and process them to profile and understand users, and they are placed inside our home. I refer to them as intelligent personal and home assistants, or IPHAs.  This research applies multidisciplinary resources to explore the phenomenon of IPHAs from two perspectives. From a more socio-technical angle, the research reflects upon what happens to the private sphere and the home once IPHAs enter it. To do so, it looks at theories and concepts borrowed from history, behavioural science, STSs, philosophy, and behavioural design. All these disciplines contribute to highlight different attributes that individuals and society associate with the private sphere and the home. When the functioning of IPHAs is mapped against these attributes it is possible to identify where Alexa and Assistant might have an impact: there is a potential conflict between the privacy expectations and norms existing in the home (as sanctuary of the private sphere) and the marketing interests introduced in the home by IPHAs’ profiling. Because of the voice-interaction, IPHAs are also potentially highly persuasive, can influence and manipulate users and affect their autonomy and control in their daily lives. From the legal perspective, the research explores the application of the GDPR and proposal for e-Privacy Regulation to IPHAs, as legislative tools for the protection of the private sphere in horizontal relationships. The analysis focuses in particular on those provisions whose application to IPHAs is more challenging, based on the technology but also on the sociotechnical analysis above. Special attention is dedicated to the consent of users to the processing, the general principles of the GDPR, attributing the role of controllers or processors to the stakeholders involved, profiling and automated decisions, data protection by design and default, as well as spam and robocalls. For some of the issues, suggestions are offered on how to interpret and apply the legal framework, in order to mitigate undesired effects. This is the case, for instance, of determining whether the owners of IPHAs should be considered controllers vis-à-vis the data of their guests, or of the implications of data protection by design and default on the design of IPHAs. Some questions, however, require a wider debate at societal and political level. This is the case of the behavioural design techniques used to entice users and stimulate them to use the vocal assistants, which present high levels of persuasion and can affect the agency and autonomy of individuals. The research brings forward the necessity to determine where the line should be drawn between acceptable practices and unacceptable ones