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Mrs Pip Cornelius

Job: Senior Lecturer - Phonetics and Phonology

School/department: School of Allied Health Sciences

Research group(s): Human Communication Studies

Address: Â鶹ƵµÀ, The Gateway, Leicester, LE1 9BH

T: +44 (0)116 257 7830

E: pcornelius@dmu.ac.uk

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Publications and outputs


  • dc.title: Children and young adults with profound and multiple learning disabilities: Evidence of intelligible subvocal language dc.contributor.author: Woods, Rosemary H.; Kerr, David; Woods, L. F.; Raghavan, Ragu; Cornelius, Pip; Brown, Adam dc.description.abstract: Introduction Literature to date describes people with Profound and Multiple Learning Disabilities (PMLD) as pre-linguistic. In contrast, this study explores the existence and use of meaningful sub vocal (SV) language by twenty PMLD participants. Method The SV utterances of 20 PMLD participants were recorded and amplified. Recordings were investigated for evidence of language content and structure, listener intelligibility, and acoustic and phonetic features relative to normal speech and whisper. Results Language content and structure was identified. Listener intelligibility was demonstrated. Acoustic and phonetic features relative to normal speech and whisper were evident. Conclusion Twenty PMLD participants produced meaningful SV language intelligible to listeners. This study requires further robust research to fully confirm its findings but highlights implications for clinical practice and for understanding of PMLD communication competencies. This paper is accompanied by audio samples and transcriptions of recorded utterances to demonstrate the SV language produced by the participants. The quality of the samples varies due to the difficulties in recording SV utterances and the difficulties for participants in articulating clearly. This is not normal speech, but it is normal language. The listener may need to replay samples where the quality of the recording is poor. dc.description: open access article

  • dc.title: Robust Impaired Speech Segmentation Using Neural Network Mixture Model dc.contributor.author: Iliya, Sunday; Neri, Ferrante; Menzies, Dylan; Cornelius, Pip; Picinali, Lorenzo dc.description.abstract: This paper presents a signal processing technique for segmenting short speech utterances into unvoiced and voiced sections and identifying points where the spectrum becomes steady. The segmentation process is part of a system for deriving musculoskeletal articulation data from disordered utterances, in order to provide training feedback for people with speech articulation problem. The approach implement a novel and innovative segmentation scheme using artificial neural network mixture model (ANNMM) for identification and capturing of the various sections of the disordered (impaired) speech signals. This paper also identify some salient features that distinguish normal speech from impaired speech of the same utterances. This research aim at developing artificial speech therapist capable of providing reliable text and audiovisual feed back progress report to the patient.

  • dc.title: Differential Evolution Schemes for Speech Segmentation: A Comparative Study dc.contributor.author: Iliya, Sunday; Neri, Ferrante; Menzies, Dylan; Cornelius, Pip; Picinali, Lorenzo dc.description.abstract: This paper presents a signal processing technique for segmenting short speech utterances into unvoiced and voiced sections and identifying points where the spectrum becomes steady. The segmentation process is part of a system for deriving musculoskeletal articulation data from disordered utterances, in order to provide training feedback. The functioning of the signal processing technique has been optimized by selecting the parameters of the model. The optimization has been carried out by testing and comparing multiple Differential Evolution implementations, including a standard one, a memetic one, and a controlled randomized one. Numerical results have also been compared with a famous and efficient swarm intelligence algorithm. For the given problem, Differential Evolution schemes appear to display a very good performance as they can quickly reach a high quality solution. The binomial crossover appears, for the given problem, beneficial with respect to the exponential one. The controlled randomization appears to be the best choice in this case. The overall optimized system proved to segment well the speech utterances and efficiently detect its uninteresting parts.

  • dc.title: Articulatory phonetics. dc.contributor.author: Knight, Rachael-Anne; Setter, Jane; Cornelius, Pip

  • dc.title: Sensory Articulation Speech System: SASSY – A 3D Animation Based Therapeutic Application For Motor Speech Disorders dc.contributor.author: Cornelius, Pip; Higgett, N.; Kaleem, R.

  • dc.title: Holography as phonetics teaching resource dc.contributor.author: Cornelius, Pip

  • dc.title: Book Review: Persisting Speech Difficulties in Children: Children's Speech and Literacy Difficulties, Book 3 dc.contributor.author: Cornelius, Pip

  • dc.title: SASSy: Sensory Articulation Speech System dc.contributor.author: Cornelius, Pip

  • dc.title: Sensory articulation speech system: SASSy - a 3D animation based therapeutic application for motor speech disorders. dc.contributor.author: Cornelius, Pip; Higgett, N.; Kaleem, R.

Research interests/expertise

  • Learning and teaching
  • Multimedia applications for speech training in clinical settings. 

Honours and awards

  • 2006 - Vice Chancellor's Distinguished Teaching Award - Teaching excellence
  • 2009 - Teacher Fellow - Teaching excellence

Membership of professional associations and societies

  • British Association of Clinical Linguistics (BACL)
  • British Association of Applied Linguistics (BAAL)

Conference attendance

2011

SASSy: Sensory Articulation Speech System Presentation at BAAL - Bristol University

2010

SASSy: Sensory Articulation Speech System Presentation at Interactive Technologies and Games: Education, Health and Disability Conference - Nottingham Trent University

SASSy: Sensory Articulation Speech System Presentation at DMU RIF event - Â鶹ƵµÀ

What is a Dissertation? Presentation to Faculty of Humanities - Â鶹ƵµÀ

2009

Is assessment the start of a slippery slope? Presentation at the International Conference of the Royal College of Speech and Language Therapy

2008

TQEF Report: How students learn phonetics

Can phonetic ability be predicted? Presentation at the International Conference of the British Association of Academic Linguistics: Reading

Consultancy work

  • Articulatory and Acoustic Phonetics Workshops provided for Leicester Speech and Language Therapy Service (last provided in 2008)

Current research students

Shuang Zu - PhD Second Supervisor

Internally funded research project information

  • 'How do Students Learn Phonetics?' TQEF January - July 2008
  • 'Developing a Multimedia Resource for Phonetics Training' HEA funding for Teacher Fellows, August 2009 - July 2010
  • 'SASSy: Sensory Articulation Sppech System' RIF, January 2008 - July 2010