A very useful general source of information is the Website paperswithcode.com which provides an organized list of potential project topics with many links to relevant research papers and datasets.
Text Classification
Chapters on logistic
regression for text and
neural network classifiers and language models
from Jurafsky and Martin, 3rd ed., 2022
Chapters on text classification
and naive Bayes and
vector-based
classification from Manning et al, 2009
Comprehensive survey paper on text classification algorithms by Aggarwal and Zhai (2012)
Neural Network Methods for Natural Language Processing, Yoav Goldberg, 2017. Covers multiple aspects of neural networks for text analysis.
Overview of general
principles in machine learning from Goodfellow et al (2016)
Tutorial paper on multi-label classification methods by de Carvalho and Freitas
Sentiment Analysis
Chapter on naive
Bayes and sentiment classification and
lexicon-based methods for sentiment analysis
from Jurafsky and Martin
Very extensive tutorial materials
on sentiment analysis by Christopher Potts including detailed instructions about using
word lexicons.
Survey paper on sentiment analysis
by Pang and Lee (2008)
Text on sentiment analysis and opinion mining
by Liu (2012)
Language Models
Chapters on n-gram language models
from Jurafsky and Martin, 3rd ed., 2022
Sequential Models and Recurrent Neural Networks
Chapters on recurrent neural networks and
encoder-decoder models
from Jurafsky and Martin, 3rd ed., 2022
Chapter on recurrent
and recursive neural networks from Goodfellow et al (2016)
Interesting
blog post on recurrent neural networks by Andrej Karpathy (2015)
Chatbots
Chapter on dialog systems and chatbots
from Jurafsky and Martin
Chatbot tutorial in Pytorch
Overview of
the Microsoft Cortana dialog management system, Sarikaya et al, 2016
Vector Embeddings and Topic Models
Chapter on dense vector
representations and embeddings for words from Jurafsky and Martin
Short text on topic models by Boyd-Graber, Hu, and Mimno (2017). Chapter 1 provides a brief introduction to topic modeling
Overview paper on topic modeling by Dave Blei (2012) and his
Webpage
on topic modeling
Chapter on latent
semantic indexing from Manning et al
Automated Speech Recognition (ASR)
Chapter on automatic speech recognition
from Jurafsky and Martin
Python speech recognition library
Blog posts on
using the Kaldi ASR system and
speech recognition in Python in general
Text Summarization
Review paper from 2020 on recent approaches for automatic text summarization.
Another recent (2020) review paper on automatic text summarization.
Older but comprehensive survey of text summarization techniques by Nenkova and McKeown, from 2012
Research paper on specialized techniques for summarization of short texts (such as reviews)
from authors at Microsoft Research and collaborators (2016)
Natural Language Generation, Text Synthesis
Recent detailed survey (2020) covering many different approaches to text generation.
Survey of recent research in natural language generation methods, Gatt and Krahmer (2018)
Question Answering
Chapter on techniques
for automated question-answering systems from Jurafsky and Martin
Wide variety of datasets and papers on question-answering systems
Paper on
toy tasks for developing question-answering systems by Weston et al (2016)
Information Extraction
Chapter on information
extraction from Jurafsky and Martin
Research paper on
extracting information about different aspects of product from reviews by Zha et al (2014)
Research paper on extracting information
from scientific articles
Document Clustering
Chapters on flat clustering
algorithms and hierarchical
clustering algorithms for text documents, from Manning et al
A technical report describing a systematic comparison of text document clustering techniques.