Frequency-Specific Temporal Envelope and Periodicity Components for Lexical Tone Identification in Cantonese

• DOI: 10.1097/aud.0b013e31803153ac
• Publication Date: 2007-03-15T07:58:37Z
• Authors: Kevin C. P. Yuen; Meng Yuan; Tan Lee; Sigfrid Soli; Michael C. F. Tong; Charles A. van Ha...
• Keywords: Adult; Periodicity; Time Factors; Vocabulary; 01 natural sciences; Asian People; Phonetics; 0103 physical sciences; Speech Discrimination Tests; Speech Perception; Audiometry, Pure-Tone; Humans

Temporal envelope and periodicity components (TEPC) in the speech signal have potentials to offer important cues for speech recognition especially in tonal languages. The aims of this study are: (i) to investigate the degree of contributions of TEPC to lexical tone identification in Cantonese; and (ii) to investigate whether or not the contributions vary among different frequency bands. The results of these investigations would reveal if there are any frequency-specific TEPC that are important for lexical tone identification.TEPC of monosyllable words carrying different lexical tones, were extracted by the method of full-wave rectification and low-pass filtering. They were used to modulate a speech spectrum noise to create the test stimuli. Thus the stimuli contain only temporal envelope and periodicity components but no temporal fine structures of the original speech signal. Multiple sets of stimuli were created with different combinations of TEPC modulated frequency bands, Eighteen adult subjects with normal hearing participated in the study.Lexical tone identification was the best when only the TEPC from the two high frequency bands (1-2 kHz and 2-4 kHz) of the original signal were provided, but the worst when only the TEPC from the two low frequency bands (60-500 Hz and 500-1000 Hz) were provided. The findings suggested that high frequency bands are carrying TEPC which are important for lexical-tone identification. Lexical tone identification performance was better for the male stimuli than the female ones.The results indicate the potential on improving speech recognition in tonal languages by manipulating TEPC via new signal processing algorithms in hearing prosthesis.