Part II - NATURAL LANGUAGE PROCESSING

DATE
TOPIC
MATERIALS
2/10
3/10
9/10
 COMPUTATIONAL PHONETICS and
SPEECH PROCESSING:
  • Speech samples: properties and acoustic measures
  • Analysis in the frequency domain, Spectrograms
  • Applications in the acoustic phonetic field.
  • Speech recognition with HMM and Deep Neural Networks
  • Spoken Dialogue Systems (ChatBots)
 - RJ - Chapter 2
- Slides (II.1), Link
- Slides (II.2), (II.3), (II.3b)
- Tutorial [Knill, 2015, part 1, part 2]
- [FT] - Chapter 8
9/10
 Tokenisation and Sentence splitting - Slides (II.4),
- [Schmid, 2008]
10/10
 COMPUTATIONAL MORPHOLOGY:
  • Morphological operations
  • Static lexica, Two-level morphology using FSA
 - Slides (II.5)
- Beesley & Karttunen [2000] Tutorial, Chap. 1
- [FT] - Section 6.2
10/10
11/10
16/10
 COMPUTATIONAL SYNTAX:
 - [FT] - Sections 6.3, 6.4, 7.1
- [SLP3] - Chapter 8, 17, 18
- Slides (II.5) (II.5b) (II.6)
- Paper [Tamburini, 2016]
17/10
18/10
 COMPUTATIONAL SEMANTICS:
  • Lexical semantic resources:
    WordNet and FrameNet.
  • Word Sense Disambiguation.
  • Distributional Semantics & Word-Space models.
  • Word, Sentence and Document embeddings.
  • Distributional approaches to sentence/text semantics.
 - [FT] - Chapter 4, Sections 6.6, 6.7
- [SLP3] - Chapter 23
- Slides (II.7), (II.8) (II.9)
- [Miller et al. 93] (only the 1st and 2nd papers)
- [Miller Fellbaum 2007]
- FrameNet site
- Paper [Lenci, 2008]
- Chap. 1-4 PhD Thesis [Sahlgren, 2006]
- Papers [Mikolov et al. 2013; Le, Mikolov 2014]
- Chap. 1, 2 and 4 from [Liu, 2020]

REFERENCES

[FT]
Tamburini, F. (2022). Neural Models for the Automatic Processing of Italian, Bologna: Pàtron.

[SLP3]
D. Jurafsky and J.H. Martin (in press). Speech and Language Processing, Prentice Hall. (3rd edition DRAFT)