MSc Computer Science with Speech and Language Processing

Overview

Start date: 24 September 2018 (intro week starts 17 September 2018)
Duration: 12 Months full time
Programme code: COMT127

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headThe capabilities of computational speech and language processing (SLP) have grown substantially in recent years, both in the research laboratory and in the commercial marketplace. There are now a wide range of applications for SLP systems such as automatic translation between languages (e.g. Arabic and English), automatic speech recognition, automatic answering of questions, text mining (e.g. from the web) and access to information through spoken human-computer dialogue. Systems which use speech and language processing are now in everyday use, through technologies such as internet search engines and mobile phones, and most major international computer and telecoms companies now engage in SLP research and development. As a result, there is strong demand for graduates with the highly-specialised multi-disciplinary skills that are required in SLP, both as practitioners in the development of SLP applications and as researchers into the advanced capabilities required for next-generation SLP systems.

Research-led teaching to enhance your career

The Department of Computer Science is an internationally recognised centre for speech and language research, with particular interests in the fields of speech technology, natural language processing and dialogue systems. This programme has close links with the Speech and Hearing and Natural Language Processing groups, the two largest research groups in the Department of Computer Science, and is principally taught by staff from these groups. Students on the course have exclusive use of their own computer lab in addition to access to general facilities within the department and university.

Why Computer Science with Speech and Language Processing at Sheffield?

  • Be in demand - there is a high demand for graduates with speech and language processing skills
  • Access to a dedicated employability team
  • Teaching informed by researchers working in relevant areas such as speech and hearing and natural language processing
  • The Department of Computer Science is 5th in the UK for Research Excellence (REF 2014)
  • 94% National Student Satisfaction ranking
Content

Please note that the course details set out here may change before you start, particularly if you are applying significantly in advance of the course start date.

Teaching is carried out in in a research-led environment. This means that you will study the most advanced theories and techniques in the field, and also have the opportunity to use state- of-the-art software tools. You will also have opportunities to engage in research-level activity through in-depth exploration of chosen topics and through your dissertation.

Core Modules

Text Processing

This module introduces fundamental concepts and ideas in natural language text processing, covers techniques for handling text corpora, and examines representative systems that require the automated processing of large volumes of text. The course focuses on modern quantitative techniques for text analysis and explores important models for representing and acquiring information from texts.

Speech Processing

This module aims to demonstrate why computer speech processing is an important and difficult problem, to investigate the representation of speech in the articulatory, acoustic and auditory domains, and to illustrate computational approaches to speech parameter extraction. It examines both the production and perception of speech, taking a multi-disciplinary approach (drawing on linguistics, phonetics, psychoacoustics, etc.). It introduces sufficient digital signal processing (linear systems theory, Fourier transforms) to motivate speech parameter extraction techniques (e.g. pitch and formant tracking).

Speech Technology

This module introduces the principles of the emergent field of speech technology, studies typical applications of these principles and assesses the state of the art in this area. Students will learn the prevailing techniques of automatic speech recognition (based on statistical modelling); will see how speech synthesis and text-to-speech methods are deployed in spoken language systems; and will discuss the current limitations of such devices. The module will include project work involving the implementation and assessment of a speech technology device.

Machine Learning and Adaptive Intelligence

The module is about core technologies underpinning modern artificial intelligence. The module will introduce statistical machine learning and probabilistic modelling and their application to describing real world phenomena. The module will give students a grounding in modern state of the art algorithms that allow modern computer systems to learn from data.

Natural Language Processing

This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing (NLP). We will cover standard theories, models and algorithms, discussing competing solutions to problems, describing example systems and applications, and highlighting areas of open research.

Research Methods and Professional Issues

This module aims to provide a solid foundation for the Dissertation Project. Students receive instruction both through taught lectures, and from their project tutors on an individual weekly basis, including: advice on research methods and technical writing style; risk analysis and contingency planning; peer-review processes; and the details of working within a professional, legal and ethical framework. The module is assessed on the basis of a project background report, which is submitted at the end of the spring semester, and on additional peer-review activities.

Team Software Project This team project aims to provide insights and wider context for the more practical aspects of the taught modules, and to provide students with experience of working in teams to develop a substantial piece of software
Dissertation Project

A wide range of dissertation topics are offered by staff teaching the course and students are also free to develop their own project ideas. Related projects chosen by students in previous years include:

  • Accent Morphing
  • High Feature Detection in Broadcast New Video
  • Voice Stress Analysis: Detection of Deception
  • Improving Information Retrieval using WordSpace
  • Question Answering from Large Text Collections
  • Search Optimisation using a Personalised Web Monitor.

Optional Modules

Students have the opportunity to take 15 credits of optional modules.  Examples of optional modules available are listed below.

Software Development for Mobile Devices

This module aims to provide a thorough grounding in the principles of software development for mobile devices. An important aim of the module is to demonstrate the real-world application of object-oriented programming principles and design patterns in software for mobile devices. Students undertake a substantial software implementation project, working in pairs. The module will be taught primarily using the Objective-C language (but students may do the assignment work using Swift if they wish to do so).

Object Oriented Programming and Software Design

This module presents the object-oriented approach to building large software systems from components in the Java Programming Language. Large scale program design and implementation issues are covered, using the Java Application Programmer's Interface, including the AWT, Swing and the Java Collections Framework. Topics include: data and procedural abstraction, collection interfaces and implementations, the event-driven model of computation, user interface components, streams and files, documentation styles with the Unified Modelling Language (UML).

The learning environment

Careers

Graduates from this course are highly valued in industry, commerce and academia. The department has good links with a number of such companies in the computational speech and language processing field, including MicroSoft, Toshiba, British Telecom, IBM, Hewlett-Packard, VoiceSignal, SoftSound, XoVox and Nuance.

The programme is also an excellent introduction to the substantial research opportunities for doctoral-level study in SLP.

Entry

Applicants for the MSc in Computer Science with Speech and Language Processing should hold at least an upper second class Honours degree, or equivalent, in a relevant discipline. This could be Computer Science, Engineering, Linguistics, Psychology or Mathematics, but other subjects may also be appropriate. Applicants are expected to have an A level or equivalent in Mathematics, and some experience of computer programming.

English language requirements

Our minimum English requirement is:

IELTS 6.5 (with no less than 6.0 in each component)
If you do not meet the entry requirements you can be considered for our pre-Masters Graduate Diploma programme.

Entry requirements

Fees and funding

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Fees and funding