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The tutorial demonstrates how to color subtitle sections based on speaker identity using Assembly AI. It starts by importing the necessary library and configuring the API key. By creating a transcriber with speaker labels enabled, the system can assign colors to each speaker's subtitles, making them visually distinct. The process involves extracting sentences, assigning colors, timestamps, and formatting them for SRT files before saving. This method enhances the subtitle experience by making it clearer who is speaking at any given time.
Configuring Assembly AI API key for transcription with speaker labels.
Illustrating subtitle format with number, timestamps, colors, and text.
Assigning colors to speakers and extracting words for subtitle chunks.
Formatting timestamps and creating structured subtitles with HTML tags.
Finalizing and saving the SRT file, confirming its generation.
Incorporating visual indicators for speaker differentiation addresses a fundamental UX challenge in media consumption. Color-coded subtitles enrich the viewing experience by providing immediate visual context. This approach aligns well with contemporary design principles that prioritize clarity and context, paving the way for more user-friendly subtitling solutions in the industry.
The service is utilized to transcribe audio with distinct speaker labels, facilitating better subtitle management.
Transcription with speaker labels enables differentiation between multiple speakers in a single audio file.
Enabling speaker labels enhances subtitle clarity by allowing visual distinctions between different speakers.
Its services help organizations streamline their audio data processing through effective transcription solutions.
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