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Learning fast adaptation on cross-accented speech recognition
Local dialects influence people to pronounce words of the same language differently from
each other. The great variability and complex characteristics of accents creates a major …
each other. The great variability and complex characteristics of accents creates a major …
Bidirectional encoder representations from transformers (BERT) language model for sentiment analysis task
The latest trend in the direction of sentiment analysis has brought up new demand for
understanding the contextual representation of the language. Among the various …
understanding the contextual representation of the language. Among the various …
Meta-transfer learning for code-switched speech recognition
An increasing number of people in the world today speak a mixed-language as a result of
being multilingual. However, building a speech recognition system for code-switching …
being multilingual. However, building a speech recognition system for code-switching …
Evaluating the rationales of amateur investors
Social media's rise in popularity has demonstrated the usefulness of the wisdom of the
crowd. Most previous works take into account the law of large numbers and simply average …
crowd. Most previous works take into account the law of large numbers and simply average …
NLP in FinTech applications: past, present and future
Financial Technology (FinTech) is one of the worldwide rapidly-rising topics in the past five
years according to the statistics of FinTech from Google Trends. In this position paper, we …
years according to the statistics of FinTech from Google Trends. In this position paper, we …
Text2timeseries: Enhancing financial forecasting through time series prediction updates with event-driven insights from large language models
Time series models, typically trained on numerical data, are designed to forecast future
values. These models often rely on weighted averaging techniques over time intervals …
values. These models often rely on weighted averaging techniques over time intervals …
An overview of financial technology innovation
In this paper, we provide an overview of financial technology (FinTech) innovation based on
our experience of organizing multiple FinTech-related events since 2018, including the …
our experience of organizing multiple FinTech-related events since 2018, including the …
Fintech for social good: A research agenda from nlp perspective
Making our research results positively impact on society and environment is one of the goals
our community has been pursuing recently. Although financial technology (FinTech) is one …
our community has been pursuing recently. Although financial technology (FinTech) is one …
Model-agnostic meta-learning for natural language understanding tasks in finance
Natural language understanding (NLU) is challenging for finance due to the lack of
annotated data and the specialized language in that domain. As a result, researchers have …
annotated data and the specialized language in that domain. As a result, researchers have …
Time series impact through topic modeling
A time-series of numerical data and a sequence of time-ordered documents are often
correlated. This paper aims at modeling the impact that the underlying themes discussed in …
correlated. This paper aims at modeling the impact that the underlying themes discussed in …