Signal Processing - January 2017 - 68

Introduction

PDAs

We are living in the mobile Internet computing cycle. During
the past decade, mobile devices have experienced unpreceWhat is a PDA?
dented growth. According to Statista [65], there are currently
A PDA is a metalayer of intelligence that sits on top of other
more than 4.6 billion mobile phone users in the world, and
services and applications and performs actions using these serthe number is expected to grow even more moving forward.
vices and applications to fulfill the user's intent. A user's intent
With this phenomenal increase in volume came technical
could be explicit, where the user commands the system to persophistication and improved capabilities of mobile devices
form an action, or it could be inferred, where the agent notifies
(both on the hardware and software sides), particularly
or makes suggestions upon evaluation of one or more triggeraround applications and web services where users can coming conditions it has been tracking. PDAs make use of some
plete a wide array of tasks. As the need and expectation to do
core set of technologies, such as machine learning, speech recmore grew, despite improvements, a limited natural user
ognition, LU, question answering (QA), dialog management
interface has remained as one of the major bottlenecks in
(DM), language generation (LG), text-to-speech (TTS) syntheinteracting with these devices. PDAs (also known as virtual
sis, data mining, analytics, inference, and personalization.
assistants) precisely target this problem and have the promise
of enhancing a user's productivity by either proactively proWhy do we need PDAs?
viding the information the user needs in the right context
PDAs are built to help the user get things done (e.g., setting up
(i.e., time and place) or reactively answering a user's quesan alarm/reminder/meeting, taking notes, creating lists) and protions and completing tasks through natural language. Tasks
vide easy access to personal/external structured data, web sercan be related to device functionality,
vices, and applications (e.g., finding the
applications, or web services.
user's documents, locating a place, making
PDAs have the promise
Research on PDA technology, howreservations, playing music). They also
of enhancing a user's
ever, started much earlier than the
assist the user in his or her daily schedule
emergence of mobile devices. Over the
and routine by serving notifications and
productivity by either
last 20 years, researchers have investialerts based on contextual information,
proactively providing
gated personalized virtual assistant agents
such as time, user location, and feeds/inforthe information the
targeting specific domains, including
mation produced by various web services,
user needs in the
tourism, elder care, device control, and
given the user's interests (e.g., commute
right context or
home and office applications [1]-[5].
alerts to/from work, meeting reminders,
reactively answering a
However, attempts at bringing them to
concert suggestions). Collectively, these
market earlier have failed because of
functionalities are expected to make the
user's questions and
their limited utility.
user more productive in managing his or
completing tasks through
Over the past five years, there has
her work and personal life.
natural language.
been tremendous investment in PDA
For example, airline travel is a comtechnology by both small and big techmonly supported scenario by most PDAs.
nology companies. Siri [17], [66], Google Now [67], CorIf the user has booked a flight and received a confirmation
tana [68], and Alexa [69] are the major personal assistants
e-mail along with an itinerary, the PDA scans the e-mail,
in the market today, and they provide proactive and/or reacextracts the flight information, and stores it on the service. On the
tive assistance to the user. Proactive assistance refers to the
day of travel, the PDA computes the user's current location using
agent taking an action to assist the user without the user's
the global positioning system (GPS) on the device, checks the
explicit request. Reactive assistance refers to the agent
traffic conditions to the airport, and tells the user when to leave
responding to the user's voice or typed command to assist
for the airport. It also checks the flight status and updates the
him or her. The number of smartphone users using PDAs
user if there is a delay, using a flight card as shown in Figure 1.
increased from 30% in 2013 to 65% in 2015 [70], indicating
Additionally, it provides weather forecasts for the destination as
increased adoption.
well as currency conversion rates. Typically, a user has to use
PDAs have become a key capability in most smartphones.
multiple applications to go through each of these steps to find out
They are now also deployed in tablets, laptops, desktop PCs,
the needed information that is listed on the cards for the travel.
and headless devices (e.g., Amazon Echo), and some are also
None of these atomic steps is significant in isolation, but stitcheven integrated into operating systems. These agents are
ing them together can potentially mark a breakthrough in usedesigned to be personal; they know their user's profile, wherefulness to the user. This is the key promise of PDAs.
abouts, schedules, and so forth. They can proactively start
interactions with their user through notifications and systemWhat is personal about PDAs?
initiated questions or reactively respond to user requests. User-
PDAs are expected to be personal. Ideally, the PDA is expectPDA interactions typically take place via natural language,
ed to know who its user is, what its user does, its user's interwhere the user speaks to the agent as if he or she were speaking
ests, what its user needs, and when and where its user needs
to a real human assistant.
it. Despite numerous efforts over the past 20 years to make
68

IEEE Signal Processing Magazine

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January 2017

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Table of Contents for the Digital Edition of Signal Processing - January 2017

Signal Processing - January 2017 - Cover1
Signal Processing - January 2017 - Cover2
Signal Processing - January 2017 - 1
Signal Processing - January 2017 - 2
Signal Processing - January 2017 - 3
Signal Processing - January 2017 - 4
Signal Processing - January 2017 - 5
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Signal Processing - January 2017 - 28
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Signal Processing - January 2017 - 65
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Signal Processing - January 2017 - 67
Signal Processing - January 2017 - 68
Signal Processing - January 2017 - 69
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Signal Processing - January 2017 - 101
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Signal Processing - January 2017 - Cover3
Signal Processing - January 2017 - Cover4
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