Coursework: Spoken Interface for Human–Robot Interaction

Weighting: 50% of module grade
Authorship: Individual

Assessed Learning Outcomes

This coursework assesses the following module learning outcomes:

LO3: Apply techniques and algorithms for spoken interfaces.

LO4: Assess concepts and challenges in spoken interfaces, particularly in robotics contexts.

Assignment Brief

You are required to design and implement a spoken interface for a robotics application, demonstrating how speech can be used to interact with or control a robot.

Your system may focus on any aspect of spoken human–robot interaction, such as:

Voice commands to control robot movement or behaviour (simulation or real robot)

Speech-based game commentary or referee assistant for robot football

Interactive dialogue system for robot coordination or teamwork

Voice-guided setup, calibration, or status reporting for a robot

You may use MATLAB, or any other software of your choice. 

This coursework has two components:

Presentation (20 points)

Technical Report (30 points)
Together they account for 50% of your final module grade.

Component 1: Presentation (20 points)

Task
Record a 10-minute video presentation in which you:

1.Present your spoken interface concept and its relevance to robotics.

2.Explain and demonstrate your developed system (code, logic, and execution).

3.Show your system interacting with spoken input in real time or simulation.

4.Reflect briefly on challenges, learning outcomes, and future improvements.

Submission Requirements

Upload a PowerPoint (.pptx) file to Canvas containing:

A link to your video presentation (e.g., YouTube or OneDrive; your face may be blurred if preferred).

A link to your code repository (e.g., GitHub).

Alternatively, you can upload your video and code directly to Canvas.

Marks awarded for:

Component 2: Technical Report (30 points)

Task
Prepare a concise technical report (up to approximately 3,000 words) documenting your spoken interface design and implementation, focusing on its application in robotics.

 Submission Requirements

Length: Up to approximately 3,000 words (about 3–6 pages, excluding references and appendices)

Format: Single-column layout, clear and professional

Font: Times New Roman or Calibri, 11 pt

Line spacing: 1.15–1.5

Margins: Standard (2.5 cm on all sides)

File type: PDF

Upload: Submit on Canvas before the deadline

Content must include:

Introduction & Motivation: The robotics context (e.g., human–robot collaboration).

System Design: Overview of speech-processing pipeline, robot integration, and interaction logic.

Implementation Details: Software tools, datasets, or speech models used.

Results & Evaluation: Demonstrate functionality, analyse strengths and limitations.

Reflections & Future Work: Discuss challenges, learning gained, and potential improvements..

References: List all cited works in a consistent style. (e.g., IEEE or APA).

Links:  Include URLs to your video presentation and code repository.

Marks awarded for:

Guidance and Recommendations

· Choose a manageable project scope; a fully integrated speech–robot system is not required — focus on a working prototype that demonstrates interaction and understanding of spoken interface principles.

Be creative — examples include:

“Speech-Based Command Sharing for Autonomous Robot”

“Spoken Command and Feedback Framework for Service Robots”

“Speech-Based Interaction Models for Social Robots”

“A Context-Aware Spoken Dialogue System for Human–Robot Teamwork”

“Spoken Dialogue System for Multi-Robot Collaboration”

Type of Feedback to be given for this assignment:

To be posted on Canvas. Individual feedback to be provided.

Information regarding the use of genAI:

Assignment Brief Template – Category 2
Unauthorised use of genAI for content creation, but allowed for proof-reading.
For this assignment you are not allowed to collaborate with AI tools, such as ChatGPT, CoPilot, Gemini, DALL-E, Midjourney etc.

Guidelines:
In this assessment you are permitted to use genAI tools (or a proofreader or proofreading service) to proofread your work but not permitted to use AI tools in the creation of content for your work. To do so would be considered to be academic misconduct.
To what extent can you use genAI tools or a proofreader or a proofreading service to help you with your assessment?
Neither a proof-reader nor a proof-reading tool (whether genAI or not) can ever be used to make changes to your work directly; the proof-reader or proof-reading tool must only identify and draw attention to possible changes which you can then choose to accept or reject; this will ensure that you remain the author of your work. 
For clarity, where a proofreader, proofreading service or genAI tool is used, they/it may only:
• identify spelling and typographical errors;
• identify poor grammar;
• highlight formatting errors or inconsistencies;
• identify errors in labelling of diagrams, charts or figures;
• identify areas for possible improvement;
• highlight a sentence or paragraph where the meaning is not clear; or draw attention to repeated phrases or omitted words.

If you use a proof-reading service, which includes an AI Tool (e.g. Grammarly) you must declare this, otherwise this would also be an academic misconduct offence under the UPR 14 App3.

Additional information:

· Regulations governing assessment offences, including Plagiarism and Collusion, are available from https://www.herts.ac.uk/__data/assets/pdf_file/0007/237625/AS14-Apx3-Academic-Misconduct.pdfLinks to an external site.Links to an external site.(UPR AS14).

· Guidance on avoiding plagiarism can be found here: https://herts.instructure.com/courses/61421(see the Referencing section)

For undergraduate modules:

o a score of 40% or above represents a pass performance at honours level.

o late submission of any item of coursework for each day or part thereof (or for hard copy submission only, working day or part thereof) for up to five days after the published deadline, coursework relating to modules at Levels 0, 4, 5, 6 submitted late (including deferred coursework, but with the exception of referred coursework), will have the numeric grade reduced by 10 grade points until or unless the numeric grade reaches or is 40.

Where the numeric grade awarded for the assessment is less than 40, no lateness penalty will be applied