Knowing the wheat from the weeds in noisy speech

This paper introduces a word boundary detection algorithm that works in a variety of noise conditions including what is commonly called the ‘cocktail party’ situation. The algorithm uses the direction of the signal as the main criterion for differentiating between desired-speech and background noise. To determine the signal direction the algorithm calculates estimates of the time delay between signals received at two microphones. These time delay estimates together with estimates of the coherence function and signal energy are used to locate word boundaries. The algorithm was tested using speech embedded in different types and levels of noise including car noise, factory noise, babble noise, and competing talkers. The test results showed that the algorithm performs very well under adverse conditions and with SNR down to -14.5dB.