Is Spoken Language All-or-Nothing?
Implications for future speech-based
human-machine interaction
Roger K. Moore
Speech and Hearing Research Group,
Dept. Computer Science, University of Sheffield,
Regent Court, 211 Portobello, Sheffield, S1 4DP, UK
r.k.moore@sheffield.ac.uk
http://www.dcs.shef.ac.uk/~roger/
Abstract. Recent years have seen significant market penetration for
voice-based personal assistants such as Apple’s Siri. However, despite
this success, user take-up is frustratingly low. This position paper ar-
gues that there is a habitability gap caused by the inevitable mismatch
between the capabilities and expectations of human users and the fea-
tures and benefits provided by contemporary technology. Suggestions are
made as to how such problems might be mitigated, but a more worri-
some question emerges: “is spoken language all-or-nothing”? The answer,
based on contemporary views on the special nature of (spoken) language,
is that there may indeed be a fundamental limit to the interaction that
can take place between mismatched interlocutors (such as humans and
machines). However, it is concluded that interactions between native and
non-native speakers, or between adults and children, or even between hu-
mans and dogs, might provide critical inspiration for the design of future
speech-based human-machine interaction.
Keywords: spoken language; habitability gap; human-machine interac-
tion
1
Introduction
The release in 2011 of Siri, Apple’s voice-based personal assistant for the iPhone,
signalled a step change in the public perception of spoken language technology.
For the first time, a significant number of everyday users were exposed to the
possibility of using their voice to enter information, navigate applications or
pose questions - all by speaking to their mobile device. Of course, voice dicta-
tion software had been publicly available since the release of Dragon Naturally
Speaking in 1997, but such technology only found success in niche market areas
for document creation (by users who could not or would not type). In contrast,
Siri appeared to offer a more general-purpose interface that thrust the potential
benefits of automated speech-based interaction into the forefront of the public’s
imagination. By combining automatic speech recognition and speech synthesis
arXiv:1607.05174v1  [cs.HC]  18 Jul 2016
2
Is Spoken Language All-or-Nothing?
with natural language processing and dialogue management, Siri promoted the
possibility of a more conversational interaction between users and smart devices.
As a result, competitors such as Google Now and Microsoft’s Cortana soon fol-
lowed1.
Of course, it is well established that, while voice-based personal assistants
such as Siri are now very familiar to the majority of mobile device users, their
practical value is still in doubt. This is evidenced by the preponderance of videos
on YouTubeTM that depict humorous rather than practical uses; it seems that
people give such systems a try, play around with them for a short while and
then go back to their more familiar ways of doing things. Indeed, this has been
confirmed by a recent survey of users from around the world which showed that
only 13% of the respondents used a facility such as Siri every day, whereas 46%
had tried it once and then given up (citing inaccuracy and a lack of privacy as
key reasons for abandoning it) [2].
This lack of serious take-up of voice-based personal assistants could be seen as
the inevitable teething problems of a new(ish) technology, or it could be evidence
of something more deep-seated. This position paper addresses these issues, and
attempts to tease out some of the overlooked features of spoken language that
might have a bearing on the success or failure of voice-based human-machine
interaction. In particular, attention is drawn to the inevitable mismatch between
the capabilities and expectations of human users and the features and benefits
provided by contemporary technical solutions. Some suggestions are made as to
how such problems might be mitigated, but a more worrisome question emerges:
“is spoken language all-or-nothing”?
2
The Nature of the Problem
There are many challenges facing the development of effective voice-based human-
machine interaction [3,4]. As the technology has matured, so the applications
that are able to be supported have grown in depth and complexity (see Fig.1).
From the earliest military Command and Control Systems to contemporary com-
mercial Interactive Voice Response (IVR) Systems and the latest Voice-Enabled
Personal Assistants (such as Siri), the variety of human accents, competing
signals in the acoustic environment and the complexity of the application sce-
nario have always presented significant barriers to practical usage. Considerable
progress has been made in all of the core technologies, particularly following the
emergence of the data-driven stochastic modelling paradigm [5] (now supple-
mented by deep learning [6]) as a key driver in pushing regularly benchmarked
performance in a positive direction. Yet, as we have seen, usage remains a serious
issue; not only does a speech interface compete with very effective non-speech
GUIs [7], but people have a natural aversion to talking to machines in public
spaces [2]. As Nass & Brave stated in their seminal book Wired for Speech [8]:
1 See [1] for a comprehensive review of the history of speech technology R&D up to,
and including, the release of Siri.
Is Spoken Language All-or-Nothing?
3
“voice interfaces have become notorious for fostering frustration and failure”
(p.6).
Fig. 1. The evolution of spoken language technology applications from early military
Command and Control Systems to future Autonomous Social Agents (robots).
These problems become magnified as the field moves forward to develop-
ing voice-based interaction with Embodied Conversational Agents (ECAs) and
Autonomous Social Agents (robots). In these futuristic scenarios, it is assumed
that spoken language will provide a “natural” conversational interface between
human beings and so-called intelligent systems. However, there many additional
challenges which need to be overcome in order to address such a requirement . . .
“We need to move from developing robots that simply talk and listen
to evolving intelligent communicative machines that are capable of truly
understanding human behaviour, and this means that we need to look
beyond speech, beyond words, beyond meaning, beyond communication,
beyond dialogue and beyond one-offinteractions.” [9] (p.321)
Of these, a perennial problem seems to be how to evolve the complexity
of voice-based interfaces from simple structured dialogues to more flexible con-
versational designs without confusing the user [10,11,12]. Indeed, it has been
4
Is Spoken Language All-or-Nothing?
known for some time that there appears to be a non-linear relationship between
flexibility and usability [13] - see Fig.2. As flexibility increases with advancing
technology, so usability increases until users no longer know what they can and
cannot say, at which point usability tumbles and interaction falls apart.
Fig. 2. Illustration of the consequences of increasing the flexibility of spoken language
dialogue systems; increasing flexibility can lead to a habitability gap where usability
drops catastrophically (reproduced, with permission, from Mike Phillips [13]). This
means that it is surprisingly difficult to deliver a technology corresponding to the
point marked ‘??’. Siri corresponds to the point marked ‘Add NL/Dialog’.
2.1
The “Habitability Gap”
Progress is being made in this area: for example, by providing targeted help to
users [14,15,16] and by replacing the traditional notion of turn-taking with a
more fluid interaction based on incremental processing [17,18]. Likewise, simple
slot-filling approaches to language understanding and generation are being re-
placed by sophisticated statistical methods for estimating dialogue states and
optimal next moves [19,20]. Nevertheless, it is still the case that there is a hab-
itability gap of the form illustrated in Fig.2.
Is Spoken Language All-or-Nothing?
5
In fact, the shape of the curve illustrated in Fig.2 is virtually identical to
the famous Uncanny Valley effect [21] in which a near human-looking artefact
(such as a humanoid robot) can trigger feelings of eeriness and repulsion in an
observer; as human likeness increases, so affinity increases until a point where
artefacts start to appear creepy and affinity goes negative. A wide variety of
explanations have been suggested for this non-linear relationship but, to date,
there is only one quantitative model [22], and this is founded on the combined
effect of categorical perception and mismatched perceptual cues giving rise to
a form of perceptual tension. The implication of this model is that uncanni-
ness - and hence, habitability - can be avoided if care is taken to align how an
autonomous agent looks, sounds and behaves [23,9]. In other words, if a speech-
enabled agent is to converse successfully with a human being, it should make
clear its interactional affordances [24,25].
This analysis leads to an important implication - since a spoken language
system consists of a number of different components, each of which possesses
a certain level of technical capability, then in order to be coherent (and hence
usable), the design of the overall system needs to be aligned to the component
with the lowest level of performance. For example, giving an automated personal
assistant a natural human voice is a recipe for user confusion in the (normal)
situation where the other speech technology components are limited in their
abilities. In other words, in order to maximise the effectiveness of the interaction,
a speech-enabled robot should have a robot voice. As Bruce Balentine
succinctly puts it [26]: “It’s better to be a good machine than a bad person”!
This is an unpopular result2, but there is evidence of its effectiveness [27], and
it clearly has implications for contemporary voice-based personal assistants such
as Siri, Google Now and Cortana which employ very humanlike voices3.
Of course, some might claim that the habitability problem only manifests
itself in applications where task-completion is a critical measure of success. The
suggestion would be that the situation might be different for applications in
domains such as social robots, education or games in which the emphasis would
be more on the spoken interaction itself. However, the argument presented in
this paper is not concerned with the nature of the interaction, rather it questions
whether such speech-based interaction can be sustained without access to the
notion of full language.
2.2
Half a Language?
So far, so good - as component technologies improve, so the flexibility of the
overall system would increase, and as long as the capabilities of the individual
2 It is often argued that such an approach is unimportant as users will habituate.
However, habituation only occurs after sustained exposure, and a key issue here is
how to increase the effectiveness of first encounters (since that has a direct impact
on the likelihood of further usage).
3 Interestingly, these ideas do appear to be having some impact on the design of
contemporary autonomous social agents such as Jibo (which has a childlike and
mildly robotic voice) [28].
6
Is Spoken Language All-or-Nothing?
components are aligned, it should be possible to avoid falling into the habitability
gap.
However, sending mixed messages about the capabilities of a spoken language
system is only one part of the story; even if a speech-based autonomous social
agent looks, sounds and behaves in a coherent way, will users actually be able
to engage in conversational interaction if the overall capability is less than that
normally enjoyed by a human being? What does it mean for a language-based
system to be compromised in some way? How can users know what they may
and may not say [29,15], or even if this is the right question? Is there such a
thing as half a language and, if so, is it habitable? Indeed, what is language
anyway?
3
What is Language?
Unfortunately there is no space here to review the extensive and, at times,
controversial history of the scientific study of language, or of the richness and
variety of its spoken (and gestural) forms. Suffice to say that human beings have
evolved a prolific system of (primary vocal) interactive behaviours that is vastly
superior to that enjoyed by any other animal [30,31,32,33,34]. As has been said
a number of times . . .
“Spoken language is the most sophisticated behaviour of the most com-
plex organism in the known universe.” [35].
The complexity and sophistication of (spoken) language tends to be masked
by the apparent ease with which we, as human beings, use it. As a consequence,
engineered solutions are often dominated by a somewhat na¨ıve perspective in-
volving the coding and decoding of messages passing from one brain (the sender)
to another brain (the receiver). In reality, languaging is better viewed as an emer-
gent property of the dynamic coupling between cognitive unities that serves to
facilitate distributed sense-making through cooperative behaviours and, thereby,
social structure [36,37,38,39,40]. Furthermore, the contemporary view is that lan-
guage is based on the co-evolution of two key traits - ostensive-inferential com-
munication and recursive mind-reading (including ‘Theory-of-Mind’) [41,42,43] -
and that abstract (mental) meaning is grounded in the concrete (physical) world
through metaphor [44,45].
These modern perspectives on language not only place strong emphasis on
pragmatics [46], but they are also founded on an implicit assumption that in-
terlocutors are conspecifics4 and hence share significant priors. Indeed, evidence
suggests that some animals draw on representations of their own abilities (ex-
pressed as predictive models [47]) in order to interpret the behaviours of others
[48,49]. For human beings, this is thought to be a key enabler for efficient recur-
sive mind-reading and hence for language [50,51].
Several of these advanced concepts may be usefully expressed in pictographic
form [52] - see Fig.3.
4 Members of the same species.
Is Spoken Language All-or-Nothing?
7
Fig. 3. Pictographic representation of language-based coupling (dialogue) between two
human interlocutors [52]. One interlocutor (and its environment) is depicted using solid
lines and the other interlocutor (and its environment) is depicted using broken lines.
As can be seen, communicative interaction is founded on two-way ostensive recursive
mind-reading (including mutual Theory-of-Mind).
8
Is Spoken Language All-or-Nothing?
So now we arrive at an interesting position; if (spoken) language interaction
between human beings is grounded through shared experiences, representations
and priors, to what extent is it possible to construct a technology that is intended
to replace one of the participants? For example, if one of the interlocutors illus-
trated in Fig.3 is replaced by a cognitive robot (as in Fig.4), then there will be an
inevitable mismatch between the capabilities of the two partners, and coupled
ostensive recursive mind-reading (i.e. full language) cannot emerge.
Fig. 4. Pictographic representation of coupling between a human being (on the left)
and a cognitive robot (on the right). The robot lacks the capability of ostensive recursive
mind-reading (it has no Theory-of-Mind), so the interaction is inevitably constrained.
Could it be that there is a fundamental limit to the language-based inter-
action that can take place between unequal partners - between humans and
machines? Indeed, returning to the question posed in Section 2.2 “Is there such
a thing as half a language?”, the answer seems to be “no”; spoken language does
appear to be all-or-nothing . . .
“The assumption of continuity between a fully coded communication
system at one end, and language at the other, is simply not justified.”
[41] (p.46).
Is Spoken Language All-or-Nothing?
9
4
The Way Forward?
The story thus far provides a compelling explanation of the less-than-satisfactory
experiences enjoyed by existing users of speech-enabled systems and identifies
the source of the habitability gap outlined in Section 2.1. It would appear that,
due to the gross mismatch between their respective priors, it might be impos-
sible to create an automated system that would be capable of a sustained and
productive language-based interaction with a human being (except in narrow
specialised domains involving experienced users). The vision of constructing a
general-purpose voice-enabled autonomous social agent may be fundamentally
flawed - the equivalent of trying to build a vehicle that travels faster than light!
However, before we give up all hope, it is important to note that there are sit-
uations where voice-based interaction between mismatched partners is successful
- but these are very different from the scenarios that are usually considered when
designing current speech-based systems. For example, human beings regularly
engage in vocal interaction with members of a different cultural and/or linguis-
tic and/or generational background5. In such cases, all participants dynamically
adjust many aspects of their behaviour - the clarity of their pronunciation, their
choice of words and syntax, their style of delivery, etc. - all of which may be con-
trolled by the perceived effectiveness of the interaction (that is, using feedback in
a coupled system). Indeed, a particularly good example of such accommodation
between mismatched interlocutors is the different way in which caregivers talk to
young children (termed “parentese”) [53]. Maybe these same principles should be
applied to speech-based human-machine interaction? Indeed, perhaps we should
be explicitly studying the particular adaptations that human beings make when
attempting to converse with autonomous social agents - a new variety of spoken
language that could be appropriately termed “robotese”6.
Of course, these scenarios all involve spoken interaction between one human
being and another, hence in reality there is a huge overlap of priors in terms
of bodily morphology, environmental context and cognitive structure, as well as
learnt social and cultural norms. Arguably the largest mismatch arises between
an adult and a very young child, yet this is still interaction between members of
the same species. A more extreme mismatch exists between non-conspecifics; for
example, between humans and animals. However, it is interesting to note that our
nearest relatives - the apes - do not have language, and this seems to be because
they do not have the key precursor to language: ostensive communication (apes
do not seem to understand pointing gestures) [41].
Interestingly, one animal - the domestic dog - appears to excel in ostensive
communication and, as a consequence, dogs are able to engage in very pro-
ductive spoken language interaction with human partners (albeit one-sided and
somewhat limited in scope) [55,41]. Spoken human-dog interaction may thus
5 Interestingly, Nass & Brave [8] noted that people speak to poor automatic speech
recognition systems as if they were non-native listeners.
6 Unfortunately, this term has already been coined to refer to a robot’s natural lan-
guage abilities in robot-robot and robot-human communication [54].
10
Is Spoken Language All-or-Nothing?
be a potentially important example of a heavily mismatched yet highly effec-
tive cooperative configuration that might usefully inform spoken human-robot
interaction in hitherto unanticipated ways.
5
Final Remarks
This paper has argued that there is a fundamental habitability problem facing
contemporary spoken language systems, particularly as they penetrate the mass
market and attempt to provide a general-purpose voice-based interface between
human users and (so-called) intelligent systems. It has been suggested that the
source of the difficulty in configuring genuinely usable systems is twofold: first,
the need to align the visual, vocal and behavioural affordances of the system, and
second, the need to overcome the huge mismatch between the capabilities and
expectations of a human being and the features and benefits offered by even the
most advanced autonomous social agent. This led to the preliminary conclusion
that spoken language may indeed be all-or-nothing.
Finally, and on a positive note, it was observed that there are situations
where successful spoken language interaction can take place between mismatched
interlocutors (such as between native and non-native speakers, or between an
adult and a child, or even between a human being and a dog). It is thus concluded
that these scenarios might provide critical inspiration for the design of future
speech-based human-machine interaction.
Acknowledgement
This work was supported by the European Commission [grant numbers EU-FP6-
507422, EU-FP6-034434, EU-FP7-231868 and EU-FP7-611971], and the UK En-
gineering and Physical Sciences Research Council [grant number EP/I013512/1].
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