SegmentVideoByTranscription
The provided Ruby code defines a module structure for a software component designed to segment a video based on its transcription output. Specifically, it's part of a sublayer of actions, with a focus on a particular action, named `SegmentVideoAction`.
### Purpose:
The primary purpose of the `SegmentVideoAction` class is to take a transcription of a video as input and process this transcription to identify distinct segments within the video. This could be valuable for indexing, searching, or categorizing video content based on topics or segments.
### Functionalities:
1. **Initialization:**
- The class is initialized with a single argument, `transcription_output`, which is expected to be a textual representation of the video's content.
2. **Core Method (`call`):**
- The main function of interest is the `call` method, which orchestrates the segmenting process by calling a helper method to analyze the transcription data.
- `perform_topic_modeling`: This private method is central to analyzing the transcription. It simulates topic modeling by naively splitting the text at double newline delimiters (\n\n) to create segments.
3. **Note on Topic Modeling Functionality:**
- The `perform_topic_modeling` method is a placeholder and does not implement actual topic modeling algorithms. In a production system, more sophisticated techniques and libraries would be utilized, such as Latent Dirichlet Allocation (LDA) or other topic analysis libraries.
### Noteworthy:
- The use of a private method encapsulates the specific logic needed to determine video segments, maintaining a clean separation of concerns within the class.
- The method assumes that transcription text is structured adequately for naive splitting might work, but sophisticated logic would handle more complex and variable formats of transcription outputs.
The code is structured well for extensibility, allowing future developers to replace or augment the placeholder segmenting logic with more advanced techniques without disrupting the overall workflow of the `SegmentVideoAction` class.
module Sublayer
module Actions
class SegmentVideoAction < Base
def initialize(transcription_output)
@transcription_output = transcription_output
end
def call
# Analyze the transcription output to determine segments
segments = perform_topic_modeling(@transcription_output)
# Further processing could go here to map segments to video timestamps
segments
end
private
def perform_topic_modeling(transcription_text)
# Placeholder method for topic modeling
# In a real-world scenario, we might use libraries like 'lda' or 'topsk'
# For simplicity, let's assume this function divides the text into segments based on some criteria
transcription_text.split("\n\n") # Naive split by double newline as example
end
end
end
end