How to Identify “Sentences” in Transcripts📝?

Have you ever noticed that YouTube transcripts doesn’t have the conventional concept of “sentences”?

Transcripts generated from live video or audio lack prior knowledge of intended scripts with punctuations. As a result, there’s no automatic delineation of “sentences” marked by punctuations.

The challenge arises when dealing with lengthy text transcripts. Imagine downloading transcripts from a video or audio without any punctuations. Wouldn’t reading a file like that make you dizzy?

In this blog post, we will explore some potential solutions to this problem, including natural language processing (NLP) techniques, machine learning models, and rule-based methods.

The Challenge

When faced with a long text with no punctuations, the task of identifying sentences becomes non-trivial. This lack of punctuation can occur in various scenarios, such as transcriptions of spoken language, informal communication, or historical texts.

The absence of sentence boundaries hinders downstream natural language processing tasks and hampers direct information consumption, making it essential to find robust methods for sentence identification in such contexts.

Importance and Use Cases

The ability to identify sentences in unpunctuated text is crucial for several applications: