Uploaded October 2013 | Updated September 2026, 21 hours ago
A central topic in spoken-language-systems research is what's called speaker diarization, or computationally determining how many speakers feature in a recording and which of them speaks when. To date, the best diarization systems have used what's called supervised machine learning: they're trained on sample recordings that a human has indexed. A new algorithm determines who speaks when in audio recordings without that training.
Source: MIT
Read more: laboratoryequipment.com/videos/2013/10/systems-knows-who%E2%80%99s-speaking
A central topic in spoken-language-systems research is what's called speaker diarization, or computationally determining how many speakers feature in a recording and which of them speaks when. To date, the best diarization systems have used what's called supervised machine learning: they're trained on sample recordings that a human has indexed. A new algorithm determines who speaks when in audio recordings without that training.
Source: MIT
Read more: laboratoryequipment.com/videos/2013/10/systems-knows-who%E2%80%99s-speaking
