Perception of Speech and Sound

Abstract

The transformation of acoustical signals into auditory sensations can be characterized by psychophysical quantities such as loudness, tonality, or perceived pitch. The resolution limits of the auditory system produce spectral and temporal masking phenomena and impose constraints on the perception of amplitude modulations. Binaural hearing (i.e., utilizing the acoustical difference across both ears) employs interaural time and intensity differences to produce localization and binaural unmasking phenomena such as the binaural intelligibility level difference, i.e., the speech reception threshold difference between listening to speech in noise monaurally versus listening with both ears. The acoustical information available to the listener for perceiving speech even under adverse conditions can be characterized using the articulation articulation index (AI) index, the speechtransmission index (STI) speech transmission index, and the speechintelligibility index (SII) speech intelligibility index. They can objectively predict speech reception thresholds as a function of spectral content, signal-to-noise ratio, and preservation of amplitude modulations in the speech waveform that enter the listenerʼs ear. The articulatory or phonetic information available to and received by the listener can be characterized by speech feature sets. Transinformation analysis allows one to detect the relative transmission error connected with each of these speech features. The comparison across man and machine in speech recognition allows one to test hypotheses and models of human speechperception speech perception. Conversely, automatic speech recognition may be improved by introducing human signal-processing principles into machine processing algorithms.