Recognition of speech under stress and in noise

Speech recognizers trained in one condition but operating in a different condition degrade in performance. Typical of this situation is when the recognizer is trained under normal conditions but operated in a stressful and noisy environment as in military applications. This paper reports on recognition experiments conducted with a "simulated stress" data base using a baseline algorithm and its modifications. These algorithms perform acceptably well (1 % substitution rate) for a vocabulary of 105 words under normal conditions, but degrade by an order of magnitude under the "stress" conditions. The experiments also show that the speech production variation caused by noise exposure at the ear is far more deleterious than ambient acoustic noise with a noise cancelling microphone.