Single band amplitude envelope cues as an aid to speechreading

Amplitude envelopes derived from speech have been shown to facilitate speech-reading to varying degrees, depending on how the envelope signals were extracted and presented and on the amount of training given to the subjects. In this study, three parameters related to envelope extraction and presentation were examined using both easy and difficult sentence materials: (1) the bandwidth and centre frequency of the filtered speech signal used to obtain the envelope; (2) the bandwidth of the envelope signal determined by the lowpass filter cutoff frequency used to “smooth” the envelope fluctuations; and (3) the carrier signal used to convey the envelope cues. Results for normal hearing subjects following a brief visual and auditory-visual familiarization/training period showed that (1) the envelope derived from wideband speech does not provide the greatest benefit to speechreading when compared to envelopes derived from selected octave bands of speech; (2) as the bandwidth centred around the carrier frequency increased from 12.5 to 1600 Hz, auditory-visual (AV) performance obtained with difficult sentence materials improved, especially for envelopes derived from high-frequency speech energy; (3) envelope bandwidths below 25 Hz resulted in AV scores that were sometimes equal to or worse than speechreading alone; (4) for each filtering condition tested, there was at least one bandwidth and carrier condition that produced AV scores that were significantly greater than speech-reading alone; (5) low-frequency carriers were better than high-frequency or wideband carriers for envelopes derived from an octave band of speech centred at 500 Hz; and (6) low-frequency carriers were worse than high-frequency or wideband carriers for envelopes derived from an octave band centred at 3150 Hz. These results suggest that amplitude envelope cues can provide a substantial benefit to speechreading for both easy and difficult sentence materials, but that frequency transposition of these signals to regions remote from their “natural” spectral locations may result in reduced performance.     

Crossmodal integration in the identification of consonant segments

Although speechreading can be facilitated by auditory or tactile supplements, the process that integrates cues across modalities is not well understood. This paper describes two “optimal processing” models for the types of integration that can be used in speechreading consonant segments and compares their predictions with those of the Fuzzy Logical Model of Perception (FLMP, Massaro, 1987). In “pre-labelling” integration, continuous sensory data is combined across modalities before response labels are assigned. In “post-labelling” integration, the responses that would be made under unimodal conditions are combined, and a joint response is derived from the pair. To describe pre-labelling integration, confusion matrices are characterized by a multidimensional decision model that allows performance to be described by a subject's sensitivity and bias in using continuous-valued cues. The cue space is characterized by the locations of stimulus and response centres. The distance between a pair of stimulus centres determines how well two stimuli can be distinguished in a given experiment. In the multimodal case, the cue space is assumed to be the product space of the cue spaces corresponding to the stimulation modes. Measurements of multimodal accuracy in five modern studies of consonant identification are more consistent with the predictions of the pre-labelling integration model than the FLMP or the post-labelling model.     

Multiple rectilinear prediction and the resolution into components

It is assumed that a battery ofn tests has been resolved into components in a common factor space ofr dimensions and a unique factor space of at mostn dimensions, wherer is much less thann. Simplified formulas for ordinary multiple and partial correlation of tests are derived directly in terms of the components. The best (in the sense of least squares) linear regression equations for predicting factor scores from test scores are derived also in terms of the components. Spearman's single factor prediction formulas emerge as special cases. The last part of the paper shows how the communality is an upper bound for multiple correlation. A necessary and sufficient condition is established for the square of the multiple correlation coefficient of testj on the remainingn—1 tests to approach the communality of testj as a limit asn increases indefinitely whiler remains constant. Limits are established for partial correlation and regression coefficients and for the prediction of factor scores.I am indebted to Professor Dunham Jackson for helpful criticism of most of this paper.