Using leap motion to investigate the emergence of structure in speech and language

© 2016, The Author(s). In evolutionary linguistics, experiments using artificial signal spaces are being used to investigate the emergenceof speech structure. These signal spaces need to be continuous, non-discretized spaces from which discrete unitsand patterns can emerge. They need to be dissimilar from—but comparable with—the vocal tract, in order tominimize interference from pre-existing linguistic knowledge, while informing us about language. This is a hardbalance to strike. This article outlines a new approach that uses the Leap Motion, an infrared controller that canconvert manual movement in 3d space into sound. The signal space using this approach is more flexible than signalspaces in previous attempts. Further, output data using this approach is simpler to arrange and analyze. Theexperimental interface was built using free, and mostly open- source libraries in Python. We provide our sourcecode for other researchers as open source

Universal principles of human communication: preliminary evidence from a cross-cultural communication game

The present study points to several potentially universal principles of human communication. Pairs of participants, sampled from culturally and linguistically distinct societies (Western and Japanese, N = 108: 16 Western-Western, 15 Japanese-Japanese and 23 Western-Japanese dyads), played a dyadic communication game in which they tried to communicate a range of experimenter-specified items to a partner by drawing, but without speaking or using letters or numbers. This paradigm forced participants to create a novel communication system. A range of similar communication behaviors were observed among the within-culture groups (Western-Western and Japanese-Japanese) and the across-culture group (Western-Japanese): They (a) used iconic signs to bootstrap successful communication, (b) addressed breakdowns in communication using other-initiated repairs, (c) simplified their communication behavior over repeated social interactions, and (d) aligned their communication behavior over repeated social interactions. While the across-culture Western-Japanese dyads found the task more challenging, and cultural differences in communication behavior were observed, the same basic findings applied across all groups. Our findings, which rely on two distinct cultural and linguistic groups, offer preliminary evidence for several universal principles of human communication

The Present Development of CsI Rich Detectors for the ALICE Experiment at CERN

The ALICE Collaboration plans to implement a 12m^2 array consisting of 7 proximity focussed C6F^14 liquid radiator RICH modules devoted to the particle identification in the momentum range: 1 GeV/c - 3.5 GeV/c for pions and kaons. A large area CSI-RICH prototype has been designed and built with the aim to validate the detector parameter assumptions made to predict the performance of the High Momentum Particle Identification System (HMPID) of the ALICE Experiment. The main elements of the prototype will be described with emphasis on the engineering solutions adopted. First results from the analysis of multitrack events recorded with this prototype exposed to hadron beams at the CERN SPS will be discussedList of FiguresFigure 1 General view of the ALICE lay-outFigure 2 Schematic layout of the fast CsI-RICHFigure 3 Perspective view of the HMPID layout with the seven RICH modules tilted according to their position with respect to the interaction vertex. The frame that supports the detectors is also shownFigure 4 Top view of the photodetector anode plane with the wire support spacer. One CsI board, out of six forming the pad cathode plane, is also shown.Figure 5 Perspective view of the HMPID honeycomb panel with the three radiator vesselsFigure 6 Cut away view of the HMPID CsI-RICH showing separately each detector component. Kapton buses that carry signals from the pads to the readout electronics are also shownFigure 7 a)number of resolved photoelectrons per event, b)reconstructed Cherenkov angle per photonFigure 8 C6F14 transmission plots before and after the molecular sieve purificationFigure 9 Display plot showing an SPS event. Three tracks are reconstructed by using the tracking chamber telescope, the associated rings are shown in the HMPID prototypeThis publication also appears as INT-98-20

A progress report on the development of the CsI-RICH detector for the ALICE experiment at LHC

The particle identification in ALICE (A Large Ion Collider Experiment) at LHC will be achieved by two complementary systems based on time of flight measurement, at low $p_t$, and on the Ring Imaging Cherenkov (RICH) technique, at $p_t$ ranging from 2 to 5 GeV/$c$, respectively. The High Momentum PID (HMPID) system will cover $\sim$5\% of the phase space, the single arm detector array beeing composed by seven 1.3$\times$1.3 m$^2$ CsI-RICH modules placed at 4.7 m from the interaction point where a density of about 50 particles/m$^2$ is expected.\\ A 1 m$^2$ prototype, 2/3 of HMPID module size, has been successfully tested at the CERN/PS beam where 18 photoelectrons per event have been obtained with 3 GeV/c pions and 10 mm liquid $\mathrm{C}_6\mathrm{F}_{14}$ radiator. Mechanical problems related to the liquid radiator vessel construction have been solved and the prototype, fully equipped, will be tested at the CERN/SPS to investigate the PID capability in high particle density events.\\ In this report, after an introductory discussion on the requirements for PID in ALICE, the HMPID prototype is described and the main results of beam tests on large area CsI photocathodes, operated in RICH detectors, are given

Timescales of Massive Human Entrainment

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend concepts of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment - as expressed by the content and patterns of hundreds of thousands of messages on Twitter - during the 2012 US presidential debates. By time locking these data sources, we quantify the impact of the unfolding debate on human attention. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient moments in the debate: Mentions in social media start within 5-10 seconds after the moment; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment.Comment: 20 pages, 7 figures, 6 tables, 4 supplementary figures. 2nd version revised according to peer reviewers' comments: more detailed explanation of the methods, and grounding of the hypothese

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

The Use of Phonetic Motor Invariants Can Improve Automatic Phoneme Discrimination

affiliation: Castellini, C (Reprint Author), Univ Genoa, LIRA Lab, Genoa, Italy. Castellini, Claudio; Metta, Giorgio; Tavella, Michele, Univ Genoa, LIRA Lab, Genoa, Italy. Badino, Leonardo; Metta, Giorgio; Sandini, Giulio; Fadiga, Luciano, Italian Inst Technol, Genoa, Italy. Grimaldi, Mirko, Salento Univ, CRIL, Lecce, Italy. Fadiga, Luciano, Univ Ferrara, DSBTA, I-44100 Ferrara, Italy. article-number: e24055 keywords-plus: SPEECH-PERCEPTION; RECOGNITION research-areas: Science & Technology - Other Topics web-of-science-categories: Multidisciplinary Sciences author-email: [email protected] funding-acknowledgement: European Commission [NEST-5010, FP7-IST-250026] funding-text: The authors acknowledge the support of the European Commission project CONTACT (grant agreement NEST-5010) and SIEMPRE (grant agreement number FP7-IST-250026). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. number-of-cited-references: 31 times-cited: 0 journal-iso: PLoS One doc-delivery-number: 817OO unique-id: ISI:000294683900024We investigate the use of phonetic motor invariants (MIs), that is, recurring kinematic patterns of the human phonetic articulators, to improve automatic phoneme discrimination. Using a multi-subject database of synchronized speech and lips/tongue trajectories, we first identify MIs commonly associated with bilabial and dental consonants, and use them to simultaneously segment speech and motor signals. We then build a simple neural network-based regression schema (called Audio-Motor Map, AMM) mapping audio features of these segments to the corresponding MIs. Extensive experimental results show that (a) a small set of features extracted from the MIs, as originally gathered from articulatory sensors, are dramatically more effective than a large, state-of-the-art set of audio features, in automatically discriminating bilabials from dentals; (b) the same features, extracted from AMM-reconstructed MIs, are as effective as or better than the audio features, when testing across speakers and coarticulating phonemes; and dramatically better as noise is added to the speech signal. These results seem to support some of the claims of the motor theory of speech perception and add experimental evidence of the actual usefulness of MIs in the more general framework of automated speech recognition

A parsimonious oscillatory model of handwriting

International audienceWe propose an oscillatory model that is theoretically parsimonious, empirically efficient and biologically plausible. Building on Hollerbach’s (Biol Cybern 39:139–156, 1981) model, our Parsimonious Oscillatory Model of Handwriting (POMH) overcomes the latter’s main shortcomings by making it possible to extract its parameters from the trace itself and by reinstating symmetry between the x and y coordinates. The benefit is a capacity to autonomously generate a smooth continuous trace that reproduces the dynamics of the handwriting movements through an extremely sparse model, whose efficiency matches that of other, more computationally expensive optimizing methods. Moreover, the model applies to 2D trajectories, irrespective of their shape, size, orientation and length. It is also independent of the endeffectors mobilized and of the writing direction

Dynamic Models of Language Evolution: The Linguistic Perspective

Language is probably the key defining characteristic of humanity, an immensely powerful tool which provides its users with an infinitely expressive means of representing their complex thoughts and reflections, and of successfully communicating them to others. It is the foundation on which human societies have been built and the means through which humanity’s unparalleled intellectual and technological achievements have been realized. Although we have a natural intuitive understanding of what a language is, the specification of a particular language is nevertheless remarkably difficult, if not impossible, to pin down precisely. All languages contain many separate yet integral systems which work interdependently to allow the expression of our thoughts and the interpretation of others’ expressions: each has, for instance, a set of basic meaningless sounds (e.g. [e], [l], [s]) which can be combined to make different meaningful words and parts of words (e.g. else, less, sell, -less ); these meaningful units can be combined to make complex words (e.g. spinelessness, selling ), and the words themselves can then be combined in very many complex ways into phrases, clauses and an infinite number of meaningful sentences; finally each of these sentences can be interpreted in dramatically different ways, depending on the contexts in which it is uttered and on who is doing the interpretation. Languages can be analysed at any of these different levels, which make up many of the sub-fields of linguistics, and the primary job of linguistic theorists is to try to explain the rules which best explain these complex combinations

Visual attention and action: How cueing, direct mapping, and social interactions drive orienting

Despite considerable interest in both action perception and social attention over the last 2 decades, there has been surprisingly little investigation concerning how the manual actions of other humans orient visual attention. The present review draws together studies that have measured the orienting of attention, following observation of another’s goal-directed action. Our review proposes that, in line with the literature on eye gaze, action is a particularly strong orienting cue for the visual system. However, we additionally suggest that action may orient visual attention using mechanisms, which gaze direction does not (i.e., neural direct mapping and corepresentation). Finally, we review the implications of these gaze-independent mechanisms for the study of attention to action. We suggest that our understanding of attention to action may benefit from being studied in the context of joint action paradigms, where the role of higher level action goals and social factors can be investigated