Improving Signal to Noise Ratio July 14th, 2010
Dealing with a poor signal to noise ratio is one of the toughest issues in automating speech recognition. At Sensory, we develop lots of techniques so our customers’ products can sit at one end of a noisy room and still recognize a speaker at the other end of the room. Our technologists typically don’t like to implement active noise cancellation techniques because of the belief that active noise cancellation’s signal processing will extract useful information from the speech data. Nevertheless we have a whole host of other techniques to make performance in noise work really well.
In Bluetooth® headsets we use a dual mic beamforming technology, and we’ve found that this approach improves our ability to recognize by about 7 or 8 dB. In the Bluetooth® space there are lots of noise cancellation providers, and there are many well proven techniques for removing noise.
What I’ve been wondering for the last few months are why those vuvuzelas are so dang loud during the World Cup broadcasts. Seems like a relatively easy task to just filter them out, or have the broadcasters microphones be in a silent booth.
I guess I’m not the only one that wondered about this: If you Google Vuvuzela, “filter” is one of the most common words following it, and clicking on it showed over 1.3 million listings from hackers guides to products for sale.