A range of new technologies have the potential to help people, whether traditionally considered hearing impaired or not. These technologies include more sophisticated personal sound amplification products, as well as real-time speech enhancement and speech recognition. They can improve user’s communication abilities, but these new approaches require new ways to describe their success and allow engineers to optimize their properties. Speech recognition systems are often optimized using the word-error rate, but when the results are presented in real time, user interface issues become a lot more important than conventional measures of auditory performance. For example, there is a tradeoff between minimizing recognition time (latency) by quickly displaying results versus disturbing the user’s cognitive flow by rewriting the results on the screen when the recognizer later needs to change its decisions. This article describes current, new, and future directions for helping billions of people with their hearing. These new technologies bring auditory assistance to new users, especially to those in areas of the world without access to professional medical expertise. In the short term, audio enhancement technologies in inexpensive mobile forms, devices that are quickly becoming necessary to navigate all aspects of our lives, can bring better audio signals to many people. Alternatively, current speech recognition technology may obviate the need for audio amplification or enhancement at all and could be useful for listeners with normal hearing or with hearing loss. With new and dramatically better technology based on deep neural networks, speech enhancement improves the signal to noise ratio, and audio classifiers can recognize sounds in the user’s environment. Both use deep neural networks to improve a user’s experiences. Longer term, auditory attention decoding is expected to allow our devices to understand where a user is directing their attention and thus allow our devices to respond better to their needs. In all these cases, the technologies turn the hearing assistance problem on its head, and thus require new ways to measure their performance.

Vehicles increasingly include features that rely on hi-tech sensors and recording; however, little is known of public attitudes toward such recording. We use two studies, an online survey (n=349) and an interview-based study (n=15), to examine perceptions of vehicle-based sensing and recording. We focus on: 1) how vehicle-based recording and sensing may differ from perceptions of current recording; 2) factors that impact comfort with vehicle-based recording for hypothetical drivers versus bystanders; and 3) perceptions of potential privacy-preserving techniques. We find that vehiclebased recording challenges current mental models of recording awareness. Comfort tends to depend on perceived benefits, which can vary by stakeholder type. Perceived privacy in spaces near cars can also impact comfort and reflect mental models of private spaces as well as the range of potentially sensitive activities people perform in and near cars. Privacypreserving techniques may increase perceived comfort but may require addressing trust and usability issues.