Natural Language Processing

Goals

This course aims to introduce students to current applications and possibilities of Natural Language Processing, both speech (audio) and text processing and enable them to be capable to perform basic tasks on natural language processing.

 

The practical sessions of the course will be based, mainly, on Python 3 and NLTK (for text) and Praat scripting language (for speech processing) and we will also use Amazon services in order to create an Alexa skill. Prior programming skills are not required.

 

Structure and Contents:

1. Natural Language Processing: from chatbots to clinical language processing

2. Text Processing

3. Speech Processing

 

Methodology

The methodology consists of several sessions in the computer lab. There will be theoretical and practical sessions, as well as a combination of both.

Assessment

The continuous assessment is based on class activities and two homework assignments.

 

The resit will consist of delivering failed assignments. Only those students who score a minimum of 3 (i.e. ranging from 3 to 4.9) can opt for the resit. The only possible final mark after the resit will be 5. The resit takes place a week after the UB evaluation period finishes (January/February).

 

One-off assessment

 

Under exceptional circumstances only one assessment activity will be set (100% of the final mark). Only those students who score a minimum of 3 (i.e. ranging from 3 to 4.9) can opt for the resit. The only possible final mark after the resit will be 5.