Endpoint detection of isolated utterances based on a modified Teager energy measurement

The authors have developed an energy measure based on Teager's energy algorithm, and have applied it to the problem of endpoint detection. This energy measure is important in that it appears to be more suitable for describing the source energy associated with the production of speech sounds than the acoustic energy typically measured, and explores a new way of viewing and using Teager's energy algorithm. Experiments were conducted on 400 utterances on which endpoint detection was expected to be difficult. Typical examples that show that this new measure is more effective than traditional measures in capturing speech events such as initial and final fricatives and plosives are presented. Whereas traditional endpoint detectors have used both (acoustic) energy and zero crossing rate, the new measure effectively combines this information into a single measure. The experimental results demonstrate that the measure can be used to improve the performance of endpoint detection algorithms and should be effective for the detection of speech in noisy environments.<
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