Journal article
Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing
A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer.
Predictions were compared to data on the intelligibility of speech presented in stationary speech-shaped noise. The model was further tested in conditions with noisy speech subjected to reverberation and spectral subtraction. Good agreement between predictions and data was found in all cases. For spectral subtraction, an analysis of the model's internal representation of the stimuli revealed that the predicted decrease of intelligibility was caused by the estimated noise envelope power exceeding that of the speech.
The classical concept of the speech transmission index fails in this condition. The results strongly suggest that the signal-to-noise ratio at the output of a modulation frequency selective process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.
Language: | English |
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Publisher: | Acoustical Society of America |
Year: | 2011 |
Pages: | 1475-1487 |
ISSN: | 15208524 , 00014966 and 01630962 |
Types: | Journal article |
DOI: | 10.1121/1.3621502 |
ORCIDs: | Dau, Torsten |
Acoustic noise Acoustic signal processing Reverberation Speech intelligibility Voice communication
Acoustic Stimulation Acoustics Adult Audiometry, Pure-Tone Audiometry, Speech Auditory Threshold Facility Design and Construction Female Humans Male Noise Nonlinear Dynamics Perceptual Masking Predictive Value of Tests Psychoacoustics Recognition, Psychology Signal Processing, Computer-Assisted Sound Spectrography Speech Acoustics Speech Intelligibility Speech Perception Time Factors Vibration Young Adult