How to Identify “Sentences” in Transcripts📝?

Angelina Yang
3 min readFeb 8, 2024

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:

1. Transcribing Audio Files: Speech-to-text transcription often yields unpunctuated text, requiring subsequent sentence boundary identification for readability and analysis.

2. Text Processing: Unpunctuated text is prevalent in social media posts, informal communication, and certain literary works. Automatic sentence identification facilitates information extraction and analysis in these domains.

3. Language Understanding Models: Training language models on diverse data, including unpunctuated text, necessitates accurate sentence boundary disambiguation to capture the underlying linguistic structure.

Potential Solutions

When dealing with a long text without any punctuations, there are two main approaches to identify sentences: adding punctuations first and then extracting sentences, or directly identifying sentences. Both methods have their own challenges and can be used based on the specific requirements of the task.