Lifeboat Foundation

Quantum mechanics dictates sensitivity limits in the measurements of displacement, velocity and acceleration. A recent experiment at the Niels Bohr Institute probes these limits, analyzing how quantum fluctuations set a sensor membrane into motion in the process of a measurement. The membrane is an accurate model for future ultraprecise quantum sensors, whose complex nature may even hold the key to overcome fundamental quantum limits. The results are published in the scientific journal, Proceedings of the National Academy of Sciences.

Vibrating strings and membranes are at the heart of many musical instruments. Plucking a string excites it to vibrations, at a frequency determined by its length and tension. Apart from the fundamental frequency — corresponding to the musical note — the string also vibrates at higher frequencies. These overtones influence how we perceive the ‘sound’ of the instrument, and allow us to tell a guitar from a violin. Similarly, beating a drumhead excites vibrations at a number of frequencies simultaneously.

These matters are not different when scaling down, from the half-meter bass drum in a classic orchestra to the half-millimeter-sized membrane studied recently at the Niels Bohr Institute. And yet, some things are not the same at all: using sophisticated optical measurement techniques, a team lead by Professor Albert Schliesser could show that the membrane’s vibrations, including all its overtones, follow the strange laws of quantum mechanics. In their experiment, these quantum laws implied that the mere attempt to precisely measure the membrane vibrations sets it into motion. As if looking at a drum already made it hum!

We all become accustomed to the tone and pattern of human speech at an early age, and any deviations from what we have come to accept as “normal” are immediately recognizable. That’s why it has been so difficult to develop text-to-speech (TTS) that sounds authentically human. Google’s DeepMind AI research arm has turned its machine learning model on the problem, and the resulting “WaveNet” platform has produced some amazing (and slightly creepy) results.

Google and other companies have made huge advances in making human speech understandable by machines, but making the reply sound realistic has proven more challenging. Most TTS systems are based on so-called concatenative technologies. This relies upon a database of speech fragments that are combined to form words. This tends to sound rather uneven and has odd inflections. There is also some work being done on parametric TTS, which uses a data model to generate words, but this sounds even less natural.

DeepMind is changing the way speech synthesis is handled by directly modeling the raw waveform of human speech. The very high-level approach of WaveNet means that it can conceivably generate any kind of speech or even music. Listen above for an example of WaveNet’s voice synthesis. There’s an almost uncanny valley quality to it.

Continue reading “Google’s DeepMind develops creepy, ultra-realistic human speech synthesis” »

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