Neural network reconstructs voices from spectrograms, alarming the NTSB
Researchers used artificial intelligence to reconstruct pilots' voices from spectrograms, the visual representations of airliner black box recordings. The system fully recovered the final words of deceased pilots with striking accuracy and crystal-clear sound. The finding alarmed the US National Transportation Safety Board (NTSB), which fears a serious violation of privacy and of the dignity of the victims' families. The agency has temporarily closed access to its public crash database.
AI-processed from TechCrunch; edited by Hamidun News
Researchers have demonstrated that a neural network can reconstruct people's voices from spectrograms of airliner black box recordings.
How does a neural network reconstruct a voice from a spectrogram?
A spectrogram is a visual representation of sound: a two-dimensional graph with time on the X axis, sound frequency on the Y axis, and color showing intensity. The neural network analyzes these patterns and recreates the original voice.
Why did the NTSB close access to the data?
Researchers demonstrated that people's voices can be reconstructed from spectrograms of black box recordings, which creates confidentiality risks. This forced the agency to rethink who should be given access to such data.
Key Questions Answered
How does a neural network reconstruct a voice from a spectrogram?
A spectrogram is a visual representation of sound: a two-dimensional graph with time on the X axis, sound frequency on the Y axis, and color showing intensity. The neural network analyzes these patterns and recreates the original voice.
Why did the NTSB close access to the data?
Researchers demonstrated that people's voices can be reconstructed from spectrograms of black box recordings, which creates confidentiality risks. This forced the agency to rethink who should be given access to such data.
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