Speaker Diarization

Sat, 18 Jul 2026 10:16:18 +0000

Definition

Speaker Diarization is the task of partitioning an audio stream into homogeneous segments according to the identity of the speaker. It combines speaker change detection with speaker clustering to label segments with unique speaker IDs. This technology is essential for making multi-party conversations understandable in transcripts, often referred to as the ‘who said what’ problem.

Summary

The process of determining ‘who spoke when’ in an audio recording.

Key Concepts

Speaker clustering
Identity labeling
Who-said-what
Audio segmentation

Use Cases

Automatic meeting minutes generation
Interview transcription
Broadcast media analysis

Automatic Speech Recognition

Sat, 18 Jul 2026 09:47:17 +0000

Definition

Automatic Speech Recognition (ASR), also known as speech-to-text, is a subfield of speech processing that leverages artificial intelligence to transcribe audio signals into written text. Modern ASR systems typically employ deep neural networks, such as recurrent neural networks or transformers, to map acoustic features to linguistic units. This technology enables voice interfaces, transcription services, and accessibility tools for hearing-impaired users.

Summary

A technology that converts spoken language into text using deep learning models.

Transcription on English AI Terms Dictionary

Speaker Diarization

Definition

Summary

Key Concepts

Use Cases

Related Terms

Automatic Speech Recognition

Definition

Summary