Exploitation of effective temporal cues for lexical tone recognition of Chinese

Lexical tone plays an important role in tonal languages. Acoustically, pitch is determined by the periodicity of speech, which is measured as the fundamental frequency (F0) of acoustic signals. In each tonal language, there are a certain number of lexical tones that are described by distinctive pitch contours. Cantonese and Mandarin have four and six tones, respectively.;People with sensorineural hearing loss have difficulty in utilizing spectral information for speech recognition and rely heavily on temporal information. The temporal information of speech is divided into three parts, based on the rate of amplitude fluctuation: temporal envelope (below 50 Hz), periodicity (50-500 Hz), and fine structure (above 500 Hz).;The goals of this thesis are to investigate what are the effective temporal cues for lexical tone perception of Chinese and how to manipulate or enhance these cues for better performance of tone perception. We adopt the research method of acoustic simulation with normal-hearing subjects. A four-channel noise-excited vocoder is used to generate test stimuli for tone identification.;We compare the contributions of temporal envelope and periodicity components (TEPCs) from different frequency regions to tone recognition in Cantonese and Mandarin. It is observed that TEPCs from high-frequency region (1-4 kHz) are more important than those from low-frequency region (< 1 kHz). In noise condition, tone recognition performance with temporal cues degrades and more spectral information is needed.;Previous studies show that hearing-impaired people have difficulties in perceiving tones, even though they are aided with cochlear implants (CIs). In this thesis, two approaches are investigated to improve Chinese tone recognition. In the first approach, TEPCs go through a process of non-linear expansion in order to increase the modulation depth of periodicity-related amplitude fluctuation. Results of listening tests show that TEPC expansion leads to a noticeable improvement on tone identification accuracy. In the second approach, the effectiveness of enhancing temporal periodicity cues in noise is investigated. Temporal periodicity cues are simplified into a sinusoidal wave with frequency equivalent to the F0 of speech. This leads to a consistent and significant improvement on tone identification performance at different noise levels. This part of research is expected to be helpful in designing CI processing strategy for effective speech perception of tonal languages.