A Model to Predict Driver Task Performance When Interacting with In-Vehicle Speech Interfaces for Destination Entry and Music Selection.

Motor vehicle crashes were estimated to be the eleventh leading cause of death in United States in 2009. Using a speech interface to operate infotainment systems while driving can potentially reduce driver distraction. Unfortunately, evaluations of driver interfaces are often too late to make changes. An alternative approach is to model driver task performance when using speech interfaces and to use the model to predict system performance early in design when changes are easier to make. The purposes of this research are to understand how drivers interact with speech interfaces and based on that knowledge, develop and validate a simulation model of how drivers interact with speech interfaces to aid speech-interface development. To develop the simulation model, a survey and a driving simulator experiment were conducted to identify how these tasks are carried out and the values for the process parameters. First, using a survey, frequency data for tasks and methods, and the content in user-generated databases were collected to assure that real tasks and constraints are considered in the simulation model. Next, a driving simulator experiment was conducted to understand how drivers perform destination entry and music selection and to determine the time drivers need to construct utterances, the errors drivers make, and the probability of correction strategies are used for each type of error. Half of these data were used to create the simulation model structure and provide the model parameters for entering destinations and selecting music using speech. Finally, the simulation model was validated for these two tasks using the second half of the data from the previous experiment. This research provides a model to predict user task performance with speech interfaces in motor vehicles. Use of this model supports the design of safer and easier to use speech interfaces in vehicles that can minimize eyes-off-road time and should reduce crash risk, and thereby protect public health. This model can be exercised to examine alternative speech interface configurations months before a physical interfaces is available for user testing when changes are easier to make, which saves time, reduces cost, and improves the quality of the interface produced.PHDIndustrial HealthUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99777/1/loe_1.pd

HTML5 and the Learner of Spoken Languages

Traditional corpora are not renowned for being user friendly. If learners are to derive maximum benefit from speech corpora, then better interfaces are needed. This paper proposes such a role for HTML5. DIT’s dynamic speech corpus, FLUENT, contains a limited series of informal dialogues between friends and acquaintances. They are characterised by naturalness and their audio quality and marked-up using a schema which allows learners to retrieve features of spoken language, such as speaker intention, formulaicity and prosodic characteristics such as speed of delivery. The requirement to combine audio assets and synchronous text animation has in the past necessitated the use of browser ‘plug-in’ technologies, such as Adobe Flash. Plug-in-based systems all suffer from major drawbacks. They are not installed by default on deployed browsers. More critically they obscure the underlying speech corpus structure. Also proprietary UIs offer no standard way of dealing with accessibility or dynamic interface reconfiguration, e.g. moving from corpus playback to concordance views. This makes design of a unified interface framework, with audio playback, synchronous text and speech, more difficult. Given the profusion of plug-in architectures and plug-in types, it is clear that such an environment is unsustainable for building tools for speech corpus visualisation. In order to overcome these challenges, FLUENT drew heavily on the HTML5 specification coupled with a user-centred design for L2 learners to specify and develop scalable, reusable and accessible UIs for many devices.This paper describes the design of the corpus schema and its close integration with the UI model

Navigation and interaction in a real-scale digital mock-up using natural language and user gesture

This paper tries to demonstrate a very new real-scale 3D system and sum up some firsthand and cutting edge results concerning multi-modal navigation and interaction interfaces. This work is part of the CALLISTO-SARI collaborative project. It aims at constructing an immersive room, developing a set of software tools and some navigation/interaction interfaces. Two sets of interfaces will be introduced here: 1) interaction devices, 2) natural language (speech processing) and user gesture. The survey on this system using subjective observation (Simulator Sickness Questionnaire, SSQ) and objective measurements (Center of Gravity, COG) shows that using natural languages and gesture-based interfaces induced less cyber-sickness comparing to device-based interfaces. Therefore, gesture-based is more efficient than device-based interfaces.FUI CALLISTO-SAR

Design and implementation of a user-oriented speech recognition interface: the synergy of technology and human factors

The design and implementation of a user-oriented speech recognition interface are described. The interface enables the use of speech recognition in so-called interactive voice response systems which can be accessed via a telephone connection. In the design of the interface a synergy of technology and human factors is achieved. This synergy is very important for making speech interfaces a natural and acceptable form of human-machine interaction. Important concepts such as interfaces, human factors and speech recognition are discussed. Additionally, an indication is given as to how the synergy of human factors and technology can be realised by a sketch of the interface's implementation. An explanation is also provided of how the interface might be integrated in different applications fruitfully

Towards a tool for the subjective assessment of speech system interfaces (SASSI)

Applications of speech recognition are now widespread, but user-centred evaluation methods are necessary to ensure their success. Objective evaluation techniques are fairly well established, but previous subjective techniques have been unstructured and unproven. This paper reports on the first stage of the development of a questionnaire measure for the Subjective Assessment of Speech System Interfaces (SASSI). The aim of the research programme is to produce a valid, reliable and sensitive measure of users' subjective experiences with speech recognition systems. Such a technique could make an important contribution to theory and practice in the design and evaluation of speech recognition systems according to best human factors practice. A prototype questionnaire was designed, based on established measures for evaluating the usability of other kinds of user interface, and on a review of the research literature into speech system design. This consisted of 50 statements with which respondents rated their level of agreement. The questionnaire was given to users of four different speech applications, and Exploratory Factor Analysis of 214 completed questionnaires was conducted. This suggested the presence of six main factors in users' perceptions of speech systems: System Response Accuracy, Likeability, Cognitive Demand, Annoyance, Habitability and Speed. The six factors have face validity, and a reasonable level of statistical reliability. The findings form a userful theoretical and practical basis for the subjective evaluation of any speech recognition interface. However, further work is recommended, to establish the validity and sensitivity of the approach, before a final tool can be produced which warrants general use