Introducing a Pictographic Language for Envisioning a Rich Variety of Enactive Systems with Different Degrees of Complexity

Moore, Roger K.

doi:10.5772/62244

Cited by 8 publications

(8 citation statements)

References 89 publications

(136 reference statements)

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“…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.…”

Section: What Is Language?mentioning

confidence: 99%

Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction

Moore

2016

Lecture Notes in Electrical Engineering

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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 argues that there is a habitability gap caused by the inevitable mismatch between the capabilities and expectations of human users and the features and benefits provided by contemporary technology. Suggestions are made as to how such problems might be mitigated, but a more worrisome 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 humans and dogs, might provide critical inspiration for the design of future speech-based human-machine interaction.

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Section: What Is Language?mentioning

confidence: 99%

Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction

Moore

2016

Lecture Notes in Electrical Engineering

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“…The phrase is inserted in a network that allows it to be activated in different ways (lexical, semantic, and visual). The diversification of activation supports the duration of the memory and therefore access to explicit memory [ 27 – 29 ]. This potential projection represents a premise for future research where it will be studied how to improve the memory for verbalized instructions formulated by simple sentences and when it is needed to restore sequential abilities in everyday life, such as brushing teeth, fastening the pants waist, and drying hands [ 70 ].…”

Section: Discussionmentioning

confidence: 99%

“…The phrase is inserted in a network that allows it to be activated in different ways (lexical, semantic, and visual). The diversification of activation supports the duration of the memory and therefore access to it [ 27 – 29 ]. There is little research that has directly examined the possibility to use sentence as a mediator in mild AD; generally, the sentence has been used to assess the problem in verbal comprehension in mild AD, as we extensively found in literature [ 30 – 33 ].…”

Section: Introductionmentioning

confidence: 99%

Sentence Context and Word-Picture Cued-Recall Paired-Associate Learning Procedure Boosts Recall in Normal and Mild Alzheimer’s Disease Patients

Iodice

Meilán

Ramos

et al. 2018

Behavioural Neurology

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Introduction The aim of this study was to employ the word-picture paradigm to examine the effectiveness of combined pictorial illustrations and sentences as strong contextual cues. The experiment details the performance of word recall in healthy older adults (HOA) and mild Alzheimer's disease (AD). The researchers enhanced the words' recall with word-picture condition and when the pair was associated with a sentence contextualizing the two items. Method The sample was composed of 18 HOA and 18 people with mild AD. Participants memorized 15 pairs of words under word-word and word-picture conditions, with and without a sentence context. In the paired-associate test, the first item of the pair was read aloud by participants and used to elicit retrieval of the associated item. Results The findings suggest that both HOA and mild-AD pictures improved item recall compared to word condition such as sentences which further enabled item recall. Additionally, the HOA group performs better than the mild-AD group in all conditions. Conclusions Word-picture and sentence context strengthen the encoding in the explicit memory task, both in HOA and mild AD. These results open a potential window to improve the memory for verbalized instructions and restore sequential abilities in everyday life, such as brushing one's teeth, fastening one's pants, or drying one's hands.

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“…In other words, there may be a fundamental limit to the complexity of the interaction that can take place between mismatched partners such as a human being and an autonomous social agent (Moore, 2016b). Although it is FIGURE 14 | Pictographic representation (Moore, 2016a) of language-based coupling (dialog) between interlocutors. In (A), communicative interaction between human beings is founded on two-way ostensive recursive mind-reading (including mutual Theory-of-Mind).…”

Section: Discussionmentioning

confidence: 99%

Toward a Needs-Based Architecture for ‘Intelligent’ Communicative Agents: Speaking with Intention

Moore

Nicolao

2017

Front. Robot. AI

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The past few years have seen considerable progress in the deployment of voice-enabled personal assistants, first on smartphones (such as Apple's Siri) and most recently as standalone devices in people's homes (such as Amazon's Alexa). Such 'intelligent' communicative agents are distinguished from the previous generation of speech-based systems in that they claim to offer access to services and information via conversational interaction (rather than simple voice commands). In reality, conversations with such agents have limited depth and, after initial enthusiasm, users typically revert to more traditional ways of getting things done. It is argued here that one source of the problem is that the standard architecture for a contemporary spoken language interface fails to capture the fundamental teleological properties of human spoken language. As a consequence, users have difficulty engaging with such systems, primarily due to a gross mismatch in intentional priors. This paper presents an alternative needs-driven cognitive architecture which models speech-based interaction as an emergent property of coupled hierarchical feedback-control processes in which a speaker has in mind the needs of a listener and a listener has in mind the intentions of a speaker. The implications of this architecture for future spoken language systems are illustrated using results from a new type of 'intentional speech synthesiser' that is capable of optimising its pronunciation in unpredictable acoustic environments as a function of its perceived communicative success. It is concluded that such purposeful behavior is essential to the facilitation of meaningful and productive spoken language interaction between human beings and autonomous social agents (such as robots). However, it is also noted that persistent mismatched priors may ultimately impose a fundamental limit on the effectiveness of speech-based human-robot interaction.

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Introducing a Pictographic Language for Envisioning a Rich Variety of Enactive Systems with Different Degrees of Complexity

Cited by 8 publications

References 89 publications

Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction

Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction

Sentence Context and Word-Picture Cued-Recall Paired-Associate Learning Procedure Boosts Recall in Normal and Mild Alzheimer’s Disease Patients

Toward a Needs-Based Architecture for ‘Intelligent’ Communicative Agents: Speaking with Intention

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