Abstract:Many elderly persons with high-frequency hearing loss find telephone use frustrating due to lower intensity levels and reductions in acoustical information that can be useful in deciphering speech. The purpose of this project is to pre-process the speech signal before it is sent over the phone line and provide speech enhancement without the use of amplifying handsets or hearing aids at the receiving end. The enhancement technique takes into account the limited bandwidth of the phone line as well as the hearing… Show more
“…As such, it was perhaps not their inability to perceive ethnicity of the callers, but circumstances made it impossible for these informants to do so. More importantly, telephone recordings lack accuracy because higher frequencies of speech, which are known for distinguishing between speakers, are lost through the telephone signals (Peterson 1952;Sheffield et al 1999), and this is especially so given the telephone technologies of the 1980s. The entire study was therefore in fact not a perception test with designed stimuli, nor was it one with some control of variables such as the ethnic group or age group of the informants and the callers.…”
Section: Research On Identification Of Ethnicity In Sgementioning
This study seeks to answer two research questions. First, can listeners distinguish the ethnicity of the speakers on the basis of voice quality alone? Second, do demographic differences among the listeners affect discriminability? A simple but carefully designed and controlled ethnic identification test was carried out on 325 Singaporean informants of the three major ethnic groups across three age groups in Singapore. The results show interesting age-related patterns in the identification of ethnicity in speakers of Singapore English. The results suggest that young Singaporeans may perhaps be deaf to ethnic variations. National policies and one's own ethnic consciousness (or lack thereof) may perhaps be responsible for creating this 'deafness'.
“…As such, it was perhaps not their inability to perceive ethnicity of the callers, but circumstances made it impossible for these informants to do so. More importantly, telephone recordings lack accuracy because higher frequencies of speech, which are known for distinguishing between speakers, are lost through the telephone signals (Peterson 1952;Sheffield et al 1999), and this is especially so given the telephone technologies of the 1980s. The entire study was therefore in fact not a perception test with designed stimuli, nor was it one with some control of variables such as the ethnic group or age group of the informants and the callers.…”
Section: Research On Identification Of Ethnicity In Sgementioning
This study seeks to answer two research questions. First, can listeners distinguish the ethnicity of the speakers on the basis of voice quality alone? Second, do demographic differences among the listeners affect discriminability? A simple but carefully designed and controlled ethnic identification test was carried out on 325 Singaporean informants of the three major ethnic groups across three age groups in Singapore. The results show interesting age-related patterns in the identification of ethnicity in speakers of Singapore English. The results suggest that young Singaporeans may perhaps be deaf to ethnic variations. National policies and one's own ethnic consciousness (or lack thereof) may perhaps be responsible for creating this 'deafness'.
“…The Departments of Speech and Hearing Science and Electrical and Computer Engineering at The Ohio State University have collaborated to develop a computerbased telephone speech-enhancement algorithm (TSEA; Komattil, 2004;Natarajan, 2002;Poling, 2004;Sheffield, 2000). The TSEA is based on a hearing aid compressionprocessing algorithm aimed at preserving spectral contrast within the speech signal (Tejero-Calado, Rutledge, & Nelson, 2001) that was chosen, in part, to amplify the signal without introducing peak clipping.…”
Results indicate that preprocessing the acoustic signal is a viable method of improving speech recognition via the telephone. The algorithm has the potential to benefit older adults with SNHL who struggle to communicate via the telephone with or without hearing aids.
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