Efficiency evaluation of robust voice control for HMI systems in the industrial production

Cars, mobile phones and smart home devices already provide an automated speech recognition (ASR) by default to keep the drivers focus on the street, to reduce complex interactions on small touch screens or to control an automation system from different rooms. However not all the benefits of these ASR consumer applications have the same impact in an industrial scenario. Different conditions and aims of HMI systems in these two fields lead to different potentials and challenges. Robust voice control, as the most natural way of communication, opens the opportunity to shorten complex command sequences and menu structures to directly execute a final command. The quantitatively influence of these effects on the production process time is not known yet. Therefore, this contribution explores which HMI scenarios benefit most from replacing or complementing existing touch screen-based interaction with robust voice control. In this contribution different typical CNC commands from CNC milling machines and industrial robots are categorized by the complexity over the menu levels and number of interactions. Afterwards the interaction time for touch screen commands and voice control commands is compared to identify the break-even-point where the robust voice control is faster than a conventional touch screen control

Characterizing individual hearing loss using narrow-band loudness compensation

Loudness is one of the key factors related to overall satisfaction with hearing aids. Individual loudness functions can reliably be measured using categorical loudness scaling (CLS) without any training. Nevertheless, the use of loudness measurement like CLS is by far less common than use of audiometric thresholds to fit hearing aids, although loudness complaints are one of the most mentioned reasons for revisiting the hearing aid dispenser. A possible reason is that loudness measurements are typically conducted with monaural narrow-band signals while binaural broad-band signals as speech or environmental sounds are typical in daily life. This study investigated individual uncomfortable loudness levels (UCL) with a focus on monaural and binaural broad-band signals, as being more realistic compared to monaural narrow-band signals. Nine normal-hearing listeners served as a reference in this experiment. Six hearing-impaired listeners with similar audiograms were aided with a simulated hearing aid, adjusted to compensate the narrow-band loudness perception back to normal. As desired, monaural narrow-band UCLs were restored to normal, however large individual deviations of more than 30 dB were found for the binaural broad-band signal. Results suggest that broad-band and binaural loudness measurements add key information about the individual hearing loss beyond the audiogram

Effizienzsteigerung: Laufwegreduzierung durch Sprachsteuerung

Studie zur Einsparung von Laufwegen in Fabrikhallen durch Sprachsteureun

Restoring perceived loudness for listeners with hearing loss

Objectives: Normalizing perceived loudness is an important rationale for gain adjustments in hearing aids. It has been demonstrated that gains required for restoring normal loudness perception for monaural narrowband signals can lead to higher-than-normal loudness in listeners with hearing loss, particularly for binaural broadband presentation. The present study presents a binaural bandwidth–adaptive dynamic compressor (BBDC) that can apply different gains for narrow- and broadband signals. It was hypothesized that normal perceived loudness for a broad variety of signals could be restored for listeners with mild to moderate high-frequency hearing loss by applying individual signal-dependent gain corrections. Design: Gains to normalize perceived loudness for narrowband stimuli were assessed in 15 listeners with mild to moderate high-frequency hearing loss using categorical loudness scaling. Gains for narrowband loudness compensation were calculated and applied in a standard compressor. Aided loudness functions for signals with different bandwidths were assessed. The deviation from the average normal-hearing loudness functions was used for gain correction in the BBDC. Aided loudness functions for narrow- and broadband signals with BBDC were then assessed. Gains for a 65 dB SPL speech-shaped noise of BBDC were compared with gains based on National Acoustic Laboratories’ nonlinear fitting procedure version 2 (NAL-NL2). The perceived loudness for 20 real signals was compared to the average normal-hearing rating. Results: The suggested BBDC showed close-to-normal loudness functions for binaural narrow- and broadband signals for the listeners with hearing loss. Normal loudness ratings were observed for the real-world test signals. The proposed gain reduction method resulted on average in similar gains as prescribed by NAL-NL2. However, substantial gain variations compared to NAL-NL2 were observed in the data for individual listeners. Gain corrections after narrowband loudness compensation showed large interindividual differences for binaural broadband signals. Some listeners required no further gain reduction for broadband signals; for others, gains in decibels were more than halved for binaural broadband signals. Conclusion: The interindividual differences of the binaural broadband gain corrections indicate that relevant information for normalizing perceived loudness of binaural broadband signals cannot be inferred from monaural narrowband loudness functions. Over-amplification can be avoided if binaural broadband measurements are included in the fitting procedure. For listeners with a high binaural broadband gain correction factor, loudness compensation for narrowband and broadband stimuli cannot be achieved by compression algorithms that disregard the bandwidth of the input signals. The suggested BBDC includes individual binaural broadband corrections in a more appropriate way than threshold-based procedures

Acoustic user interfaces for ambient-assisted living technologies

This contribution discusses technologies for acoustic user interaction in ambient-assisted living (AAL) scenarios. Acoustic user interfaces allow for a natural and convenient way to interact with technical systems e.g. via sound or speech presentation or via speech input by means of automatic speech recognition (ASR) as well as by detection and classification of acoustic events. Older persons targeted by AAL technologies especially need more easy-to-use methods to interact with inherently complex supporting technology. As an example we designed and evaluated an application for acoustic user interaction with a multi-media reminder and calendar system. For this purpose, mainly older participants were involved in user studies to continuously evaluate and support the development strictly following a user-centred design process. The results suggest a wide acceptance of acoustic user interfaces by older users either for controlling inherently complex AAL systems by using robust ASR technologies or as a natural and ambient way of presenting information to the user. However, further research is needed to increase the robustness of ASR systems when using hands-free equipment, i.e. to provide a real ambient way of interaction, and to introduce personalised speech and sound presentation schemes accounting for the individual hearing capabilities and sound preferences

Novice2Expert - a Cognitive Model within a Usability Evaluation Framework: Paper presented at 7. Interdisziplinärer Workshop Kognitive Systeme. Mensch, Teams, Systeme und Automaten 2018, 21.-22. Juni 2018, Braunschweig

The motivation of the usability evaluation framework CogUA (Cognitive Usability Analysis) is to support usability analysis processes of graphical user interfaces (GUI) based on software tools deriving objective and reproducible evaluation parameters in a partly automatic process. In the current prototype status, it consists of five modules: (i) Observer, (ii) Trace Illustrator, (iii) Screen Shot Analyser, (iv) Use Case Detector and (v) Predictor. The framework and its modules are shortly described in the paper. The focus of this paper lies on the fifth module, the Predictor. It is based on a cognitive model to simulate human users while interacting with a GUI. For the investigation, a test application is set up in which a label is presented as a task on the screen. The user, respectively the model, has to find and click the button with the presented label. The derived interaction times based on the model are compared with results of a small user study in order to evaluate the different versions of the cognitive model. Three different scenarios are investigated: (a) the model as a novice, searching each time for the correct button on the screen, (b) the model, which is able to remember the position of buttons of the GUI, and (c) the model, which is able to remember the position of buttons as well as the sequence of the tasks. The interaction time necessary to execute a specific task sequence is reduced from scenario (a) to (b) to (c). The relative reduction of interaction times derived from the user study and predicted by the model is comparable

The Lower Saxony research network design of environments for ageing : towards interdisciplinary research on information and communication technologies in ageing societies

Worldwide, ageing societies are bringing challenges for independent living and healthcare. Health-enabling technologies for pervasive healthcare and sensor-enhanced health information systems offer new opportunities for care. In order to identify, implement and assess such new information and communication technologies (ICT) the 'Lower Saxony Research Network Design of Environments for Ageing' (GAL) has been launched in 2008 as interdisciplinary research project. In this publication, we inform about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive healthcare. Although GAL's high interdisciplinarity at the beginning slowed down the speed of research progress, we can now work on problems, which can hardly be solved by one or few disciplines alone. Interdisciplinary research projects on ICT in ageing societies are needed and recommended