Abstract: 

Attendees will learn how to apply NLP to financial data. Earnings data covers all industries in the US; attendees will be surprised to learn how much information is hiding in plain sight. Earnings calls are public information and I'm going to show you what you're able to learn from them using ASR and NLP tools.

Speech recognition technology has come a long way in recent years, but there are still some larger market challenges when it comes to transcribing speech accurately. This comes into play especially for domain-specific terminology around certain industries. For example, in the renewable energy industry, transcription might include terms like “hydro DM,” “biomass conversion,” and “renewable portfolio standard,” that are outside normal conversation.

This session will focus on ASR and Natural Language Processing (NLP) for financial use cases, specifically for earnings calls. I'll speak about what can be gathered from massive collections of financial audio data (i.e. 20,000+ hours).

Session Outline:

This session is relevant for executives in almost every industry that may not fully understand their audio data is an asset, but will focus on financial applications of artificial intelligence.

There will be three takeaways for the audience:

1. Layering ASR+NLP over earnings calls is a powerful application of AI.
2. There are ways to run analyses like these at multiple levels of technical proficiency, including for data scientists, software engineers and no-code solutions for non engineers.
3. To expand, can do this type of analysis outside of finance, like in healthcare, operations, or compliance. Anywhere where there is spoken information shared we can get insights and build better products.

Bio: 

Katie is the Product Lead for Scribe at Kensho. Scribe is an Artificial Intelligence, Natural Language Processing tool that does voice to text transcription.

Katie’s background is in data pipeline management and machine learning - specifically unsupervised machine learning in aerospace to detect satellite collisions.

She is a guest lecturer at Johns Hopkins University and graduated with distinction from the University of Virginia.