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Speech and Motor Neuroscience Group

 

HomeMembers | ResearchParticipate Publications

 

Please note that all the documents made available here are for non-commercial use only. 
The copyright holders maintain the copyright and all rights.

 

Journal Articles

 

Howard IS, Franklin S & Franklin DW (2020)

Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system

PLOS ONE

https://doi.org/10.1371/journal.pone.0228083

HowFraFraPLOSONE2020.pdf

 

Francis, K. B., Gummerum, M., Ganis, G., Howard, I. S., & Terbeck, S. (2019).

Alcohol, empathy, and morality: acute effects of alcohol consumption on affective empathy and moral decision-making

Psychopharmacology

Francis_et_al-2019-Psychopharmacology.pdf

 

Francis, K. B., Gummerum, M., Ganis, G., Howard, I. S., & Terbeck, S. (2018).

Virtual morality in the helping professions: Simulated action and resilience.

British Journal of Psychology, 109(3), 442-465.

FrancisBjop.12276.pdf

 

Francis, K., Terbeck, S., Briazu, R., Haines, A., Gummerum, M., Ganis, G. &  Howard, I. S. (2017)

Simulating Moral Actions: An Investigation of Personal Force in Virtual Moral Dilemmas.

Scientific Reports | 7: 13954 | DOI:10.1038/s41598-017-13909-9

FraTerBriHaiGumGanHow2017.pdf

 

Howard IS, Ford C, Cangelosi A & Franklin DW (2017)

Active lead-in variability affects motor memory formation and slows motor learning

Scientific Reports 7, Article number: 7806(2017) doi:10.1038/s41598-017-05697-z

HowForCanFra_SR_2017.pdf                                         

Example media coverage:

Daily Mail

Medical Xpress

 

Francis KB, Howard C, Howard IS, Gummerum M, Ganis G, Anderson G, Terbeck S. (2016)

Virtual Morality: Transitioning from Moral Judgment to Moral Action?

PLoS ONE, 2016 Oct 10;11(10):e0164374. doi: 10.1371/journal.pone.0164374

FraHowHowGumGanAndTer_PO_2016.pdf

Example media coverage:

Daily Mail

Medical Daily

Medical Xpress

 

Howard IS & Franklin DW (2016)

Adaptive tuning functions arise from visual observation of past movement

Scientific Reports 6, Article number: 28416 (2016) doi:10.1038/srep28416

HowFra_SciRep_2016.pdf

 

Carroll TJ, de Rugy A, Howard IS, Ingram JN & Wolpert DM (2016) 
Enhanced cross-limb transfer of force field learning for dynamics that are identical in extrinsic and joint-based coordinates for both limbs
Journal of Neurophysiology

Carroll_et_al_2016.pdf

 

Messum P & Howard IS (2015)

Creating the cognitive form of phonological units: the speech sound correspondence problem in infancy could be solved by mirrored vocal interactions rather than by imitation

Journal of Phonetics

MesHow_JoP_2015

 

Howard IS & Franklin DW (2015)

Neural tuning functions underlie both generalization and interference

PLoS ONE, 10(6), e0131268.

HowFra_PLOSONE_2015.pdf

 

Howard IS, Wolpert DM & Franklin DW (2015)

The value of the follow-through derives from motor learning depending on future actions (with corrected figures)

Current Biology: doi:10.1016/j.cub.2014.12.037

HowWolFra_CB_2015.pdf

Supplementary Material

Current Biology Commentary by Miall RC, R106-8

 

­­­­­­­­­­­­­­­­­­­Howard IS & Messum P (2014)

Learning to pronounce first words in three languages: an investigation of caregiver and infant behavior using a computational model of an infant.

PLoS ONE 9(10): e110334. doi:10.1371/journal.pone.011033

HowMes_PLOSONE_2014.pdf

Supplementary material

 

Howard IS, Wolpert DM & Franklin DW (2013)

The effect of contextual cues on the encoding of motor memories

Journal of Neurophysiology

HowWolFra_JNS_2013.pdf


Howard IS, Ingram JN, Franklin DW & Wolpert DM (2012),
Gone in 0.6 seconds: The encoding of motor memories depends on recent sensorimotor states,
Journal of Neuroscience 32(37):12756-12768.
HowIngFraWol_JNS_2012.pdf

 

Messum P & Howard IS (2012),
Speech Development: Toddlers Don't Mind Getting it Wrong,
Current Biology 22(5), R160–R161.
MesHow_CB_2012.pdf

 

Ingram JN, Howard IS, Flanagan JR & Wolpert DM (2011),
A context-dependent multi-state learning process underlies rapid adaptation to familiar object dynamics,
PLoS Computational Biology 7(9): e1002196.
IngHowFlaWol_PCB_2011.pdf

 

Howard IS, Ingram JN & Wolpert DM (2011),
Separate representations of dynamics in rhythmic and discrete movements: Evidence from motor learning,
Journal of Neurophysiology 105, 1722-1731.
HowIngWol_JNP_2011.pdf
Supplementary material

 

Howard IS & Messum P (2011),
Modeling the development of pronunciation in infant speech acquisition,
Motor Control 2011, 15, 85-117.
HowMes_MC_2011.pdf
Supplementary material

 

Howard IS, Ingram JN & Wolpert DM (2010),
Context dependent partitioning of motor learning in bimanual movements,
Journal of Neurophysiology 104, 2082-2091.
HowIngWol_JNP_2010.pdf
Supplementary material

 

Ingram JN, Howard IS, Flanagan JR & Wolpert DM (2010),
Multiple grasp-specific representations of tool dynamics mediate skilful manipulation,
Current Biology 20(7): 618-623.
[IngHowFlaWol2010.pdf]
Supplementary information for paper

 

Howard IS, Ingram JN, Körding KP & Wolpert DM (2009),
The statistics of natural movements are reflected in motor errors,
Journal of Neurophysiology 102 (3), 1902-1910.
HowIngKorWol2009.pdf
Supplementary material

 

Howard IS, Ingram JN & Wolpert DM (2009),
A modular planar robotic manipulandum with end-point torque control,
Journal of Neuroscience Methods 181, 199-211.
HowardJNM2009.pdf
Supplementary material

 

Howard IS, Ingram JN & Wolpert DM (2008),
Composition and decomposition in bimanual dynamic learning,
Journal of Neuroscience 28 (42): 10531-10540.
HowIngWol08.pdf

 

Ingram JN,Körding KP, Howard IS, Wolpert DM (2008),
The statistics of natural hand movements, 
Experimental Brain Research, Volume 188, Number 2 / June, 2008.
IngKorHowWol2008.pdf

 

Howard IS & Huckvale MA (2005),
Learning to Control an Articulator Synthesizer by Imitating Real Speech,
ZAS Papers in Linguistics 40, 2005: 63-78
, Berlin, Germany. 
HowHucZAS05.pdf

 

Körding KP, Fukunaga IS, Howard I, Ingram JN & Wolpert DM (2004),
A neuroeconomics approach to inferring utility functions in sensorimotor control,
Public Library of Science: Biology 2(10) e330.
PLOS2004Kording

 

Walliker JR & Howard IS (1990),
Real-time portable multi-layer perceptron voice fundamental-period extractor for hearing aids and cochlear implants,
Speech Communication 9, Elsevier Science Publishers B.V (North Holland), pp63-71.
[WalHow90.pdf]

 

 

 

Conference Proceedings

 

Howard IS (2020), Speech fundamental period estimation using a neural network

ESSV 2020 Magdeburg, Germany.

ESSV2020Howard.pdf

 

Howard IS (2019), A modular 3D-printed inverted pendulum.

K. Althoefer et al. (Eds.): TAROS 2019, LNAI 11649, pp. 1–12, 2019.

HowTaros2019.pdf

SupplementaryMaterial

 

Howard IS & Birkholz P (2019)

Modeling Vowel Acquisition using the Birkholz Synthesizer

ESSV 2019 Dresden, Germany.

HowBir_ESSV_2019.pdf

 

Howard, I. S., Franklin, S., & Franklin, D. W. (2018).

Characterization of Neural Tuning: Visual Lead-in Movements Generalize in Speed and Distance.

In International Conference on NeuroRehabilitation (pp. 1030-1033). Springer, Cham.

HowFraFraIEEE_2018.pdf

 

Howard IS & Birkholz P (2018)

Using state feedback to control an articulatory synthesizer

ESSV 2018 Ulm, Germany.

HowBir_ESSV_2018.pdf

 

Howard IS (2017),

Robotic actuation of a 2D mechanical vocal tract,

ESSV 2017 Saarbrücken, Germany.

HowardESSV2017.pdf

ESSV2017SupMat

 

Howard IS (2016),

Towards a mechanical vocal apparatus for vowel production,

ESSV 2016 Leipzig, Germany.

HowardESSV2016.pdf

ESSV2016LeipzigSupMat

 

Howard IS & Messum P,
Modelling caregiver tutored development of pronunciation in a young child,
In: Kröger BJ, Birkholz P (eds.)  Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung (TUDpress, Dresden, Germany), pp.75-82.
HowMesExpESSV2011.pdf

 

Howard IS & Messum P,
The computational Architecture of Elija: A model of a young child that learns to pronounce,
In: Kröger BJ, Birkholz P (eds.) Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung (TUDpress, Dresden, Germany), pp.138-145.
HowMesMethESSV2011.pdf

 

Zacharias F, Howard IS, Hulin T, Hirzinger G (2010)
Workspace Comparisons of Setup Configurations for Human-Robot Interaction,
Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3117 – 3122.
ZacHowHulHir_IROS_2010.pdf

 

Howard IS (2009),
Building machines that learn to speak the way infants do,
Acorns Workshop 11th September, Interspeech Brighton 2009.
PositionStatementISH.pdf

 

Huckvale MA, Howard IS, Fagel S (2009),
KLAIR: a Virtual Infant for Spoken Language Acquisition Research,
Interspeech Brighton 2009.
HucHowFag2009.pdf

 

Howard IS & Messum P, (2008),
Modelling motor pattern generation in the development of infant speech production,
In: 8th International Seminar on Speech Production – (ISSP'08), edited by Sock R, Fuchs S, and Laprie Y. Strasbourg, France: INRIA 2008, pp.165-168.
HowMesISSP2008.pdf

 

Howard IS &Messum P (2007),
A Computational Model of Infant Speech Development,
In: XII International Conference "Speech and Computer" (SPECOM'2007).  Moscow, Russia: Moscow State Linguistics University, 2007, pp. 756-765
Specom2007.pdf

Howard IS & Huckvale MA (2005),
Training a Vocal Tract Synthesizer to Imitate Speech using Distal Supervised Learning,
In: 10th International Conference on Speech and Computer (SPECOM'2005).  University of Patras, Patras, Greece, 2005, pp.159–162.
Specom2005.pdf
Supplementary information for paper

Huckvale MA & Howard IS (2005),
Teaching a vocal tract simulation to imitate stop consonants,
Interspeech Lisbon 2005 Portugal, pp. 3213-3216.
eurosp2005huckvale.pdf

 

I S Howard, (1991),

Further developments of a neural network speech fundamental period estimation algorithm,

2nd International Conference, Artificial Neural Networks, November 1991, Bournemouth, England.

[How91.pdf]

 

I S HOWARD, (1990),

Two-level word recognition using the multi-layer perceptron, Proc. IOA, Windemere, 1990.

[How90.pdf]

 

I S Howard & M A Huckvale, (1989),

Two level recognition of isolated words using neural nets,

First IEE conference on Artificial Neural Networks, London.

[HowHuc89.pdf]

 

Howard IS & Huckvale MA, (1988),
Speech fundamental period estimation using a trainable pattern classifier,
FASE88.
[HowHuc88a.pdf]

 

I S Howard & M A Huckvale, (1988),

Acoustic phonetic attribute determination using multi-layer perceptrons, IEE colloquium digest 11.

[HowHuc88b.pdf]

 

I S HOWARD & M A Huckvale, (1988), Training feature detectors for use in automatic speech recognition, FASE88.

[HowHuc88c.pdf]

 

I S Howard & M A Huckvale (1987),

The application of adaptive constraint satisfaction networks to acoustic phonetic attribute determination, Proc. Euro. Confr. Sp. Tech.


[HowHuc87.pdf]

 

Howard IS & Howard DM (1986),
Quantitative comparisons between time domain speech fundamental frequency estimation algorithms
Proc. IOA, Vol 8, pp323-330.
[HowHow86.pdf]

 

 

 

PhD Thesis

 

Howard IS,
Speech fundamental period estimation using pattern classification,
PhD thesis, University of London
, [HowPhD.pdf]

 

 

Reports

 

I S Howard, (1991),

Speech fundamental period estimation using pattern classification, Speech, Hearing & Language,

Work in progress, Volume 5, University college London, Department of Phonetics and Linguistics, 1991.

[HowSHL91.pdf]

 

I S Howard, (1990),

Experiments with modular and two-level training of multi-layer perceptrons for isolated word recognition,

Speech, Hearing & Language, Work in progress, Volume 4, University college London, Department of Phonetics and Linguistics, 1990.

[HowSHL90.pdf]

 

 

Miscellaneous Articles

 

Howard IS (2014)

7-Step Guide: Writing a research article for journal publication 

ArticleWritingGuide_ISH_2014.pdf

 

Howard IS (2014)

7-Step Guide to Screencasting

ScreencastingGuide_ISH_2014.pdf

 

Copyright © 2005-2016 Ian Howard. All Rights Reserved
Last Changed:  January 2016