The TAL Laboratories are currently housed in two buildings, both on the Sidgwick Site.
Phonetics Laboratory
In the Raised Faculty Building there is a well-equipped Phonetics Laboratory, including a sound-treated room to create recordings and run experiments, a network of workstations with speech analysis software, and electropalatography for monitoring tongue movements whilst talking. The laboratory also has an airflow meter. All students taking courses in experimental phonetics and phonology will be given access to the laboratory to attend practicals and seminars, to practice their phonetics skills, and to carry out their research projects.
Contact:
- Prof. Brechtje Post (bmbp2@cam.ac.uk)
- Dr. Kirsty McDougall (kem37@cam.ac.uk)
Psycholinguistics Laboratory
The TAL laboratories also include a testing suite in the English Faculty Building which provides a venue for linguistic and psycholinguistic research. One of the suites is equipped with an electroencephalograph (EEG) which is used, for example, to study brain activities associated with language processing. The facilities also contain an Eye Link 1000 Plus Eye tracker. Its high sampling rate allows to record eye movements during reading experiments. There is also a Tobii Eye Tracker in a separate room.
Finally, all suites in the laboratory are equipped with computers that contain experimental software installed for stimulus presentation (E-prime, Superlab, Experiment Builder, and Psychopy, MATLAB) and data analysis (Python, MATLAB, Data Viewer). Students who are pursuing research in psycholinguistics and bi/multilingualism are regular users of the lab, but the Lab is also used by members of other research clusters.
Contact:
- Prof. Ianthi Tsimpli (imt20@cam.ac.uk)
- Dr . John Williams (jnw12@cam.ac.uk)
Language Technology Laboratory
TAL Laboratories also include the Language Technology Lab (http://ltl.mml.cam.ac.uk/) whose members focus on advanced natural language processing (NLP) technologies that address information challenges in society. Modern NLP requires complex machine learning models and large-scale computing resources. The LTL is equipped with state of the art computing facilities including 15 dedicated NVIDIA GPU (Graphics Processing Unit) powered workstations and terabyte-scale network attached storage. All research students working on computational linguistics have access to these in-house facilities in addition to free time on the University of Cambridge's central resources, the Peta4 and Wilkes2 clusters (https://www.hpc.cam.ac.uk/high-performance-computing). Access to a number of large international corpora (British National Corpus, ICAME, ICE, etc.), and facilities for the analysis of corpora is also provided.
Contact:
- Prof. Nigel Collier (nhc30@cam.ac.uk)
- Prof. Anna Korhonen (alk23@cam.ac.uk)