Speaker Detection & Diarization
Identifisera og merkja ymiskar talarar í tínum ljóð- og video- transkriptiónum. Vitja nágreiniliga, hvør segði hvat.
Hvat er ein lýsingarorð?
Speaker diarization is the process of partitioning a audio stream into segments according to the identity of the speaker. In simpler terms, it answers the question "who spoke when?" This is essential for multi-speaker recordings like meetings, interviews, podcasts, conference calls, and legal proceedings where knowing who said what is just as important as what was said.
STT.ai uses advanced neural speaker diarization models that can detect and label speakers in real time. The system creates speaker embeddings -- numerical representations of each voice's unique characteristics -- and clusters them to distinguish between different people. This works even when speakers have similar voices or frequently interrupt each other.
Ummæli av bókini
1. Uppsøgn av talvirksemi
Tað er ikki altíð, at tað er einans tónleikurin, ið er í fokus, men eisini lýsingar, lýsingartekstur og lýsingarmyndir.
2. Speaker Embedding
Ein lýsingarorð er eitt orð, sum verður nýtt í einum orðabókarteksti, og sum lýsir ein persón.
Clustering & Labeling
Í hesum føri verður lagið skrivað í einum flokki, sum er settur saman av tveimum stavum (1 og 2).
Use cases for speaker detection
Speaker Detection on STT.ai
Speaker detection is available on all paid plans. When you transcribe audio or video with speaker detection enabled, the transcript will include speaker labels inline with the text. You can also export speaker-labeled transcripts in all supported formats including SRT, VTT, DOCX, JSON, and PDF.
The system can detect up to 20 distinct speakers in a single recording. For best results, ensure each speaker has at least a few seconds of solo speech. Overlapping speech is handled but may reduce accuracy in heavily cross-talked segments.
Prøv at uppdaga talaran nú
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