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AssemblyAI adds speaker diarization to Speech-to-Text API

By PulseAugur Editorial · [1 sources] ·

AssemblyAI has introduced a new speaker diarization feature for its Speech-to-Text API, designed to identify and label different speakers within a single audio channel. This feature addresses the challenge of transcribing audio from sources like sales calls, clinic visits, or podcasts, where multiple individuals speak over one microphone. By automatically segmenting audio and assigning relative labels such as 'Speaker A' or 'Speaker B', the system enables more nuanced analysis of conversations, improving the utility of transcripts for various applications including sales, customer service, healthcare, and media. AI

IMPACT Enhances the utility of transcribed audio for analysis in sales, customer service, and healthcare by attributing speech to specific speakers.

RANK_REASON Product feature launch for an AI service provider.

Read on AssemblyAI blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AssemblyAI adds speaker diarization to Speech-to-Text API

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52 / 100
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Tool
Product feature launch for an AI service provider.
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. AssemblyAI blog TIER_1 English(EN) ·

    Speaker diarization: Speaker labels for mono channel files

    AssemblyAI Speech-to-Text API's Speaker Diarization (diarisation) is the process of splitting audio or video inputs automatically based on the speaker's identity. It helps you answer the question "who spoke when?".

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