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Working with Timestamps, Utterances, and Speaker Diarization in Deepgram

Blog post from Deepgram

Post Details
Company
Date Published
Author
Stephen Oladele
Word Count
3,040
Company Posts That Month
16
Language
English
Hacker News Points
-
Post removed?
No
Summary

Deepgram's speech-to-text (STT) capabilities extend beyond basic transcription by integrating metadata such as utterances, timestamps, and speaker diarization to enhance the contextual understanding of conversations. By enabling features like utterances, diarize, and smart_format in Deepgram's STT API, users can receive structured, context-aware transcripts that preserve conversational context and allow for detailed analytics like talk time and interruptions. This functionality supports the creation of speaker-aware applications, such as custom video players with colored speaker cues and searchable transcripts for QA and compliance purposes. Moreover, Deepgram offers tools for converting enriched transcripts into standard caption formats like SRT and WebVTT, facilitating media synchronization and enhancing accessibility. The guide emphasizes the importance of treating speech as structured data to unlock further value, enabling developers to build robust voice AI applications with features like searchable players, meeting assistants, and analytics dashboards.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
AI Model Fine-tuning 17 276 96 58 -51%
Voice AI 5 668 123 38 -10%
Real-time 1 4,065 968 231 -6%
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