A spectrogram is a display of the frequency content of a signal drawn so that the energy content in each frequency region and time is displayed on a coloured scale. In the case of speech signal, the spectrogram has been widely used to investigate the features of speech in the time-frequency plane that are perceptually important. For instance, more than fifty years ago, the spectrogram was already being used to determine the average frequencies of the first three formants of the vowels of American English for men, women and children [1]. The spectrogram is also widely used in speech analysis for developing speech recognition systems [2]. The spectrogram today can be generated digitally using the Short Time Fourier Transform (STFT). However, spectrograms implemented using STFT suffer from the unavoidable tradeoff between time and frequency resolution, also known as the uncertainty principle of signal analysis [3]. The emerging recognition of the existence of frequency and amplitude modulations in speech on the order of a pitch cycle, which is referred to as “fine structure”, has motivated many researchers to develop new spectrogram representations to obtain better timefrequency resolution. A filter-bank method called fine structure spectrogram (FSS) introduced in [4] is shown to be able to detect the fine structure in the modulation patterns of speech, not seen by other methods before. Although FSS is successful in utilizing some of the functional components of a real auditory system, there are other properties, which have not yet been implemented in its approach. In this paper, the fine structure spectrogram is first presented, modifications to build a more biological FSS are then introduced, and finally the results from both original and modified versions of FSS are compared to each other and in relation to the real output as processed by an actual auditory modeling system. Manuscript received in February 2007. Huawei Colin Li is a Masters candidate with the Sensory Communications Laboratory in the Institute of Biomaterials and Biomedical Engineering and Department of Electrical and Computer Engineering, University of Toronto, ON, Canada (e-mail: huawei.li@ utoronto.ca). 2. FINE STRUCTURE SPECTROGRAM

https://proceedings.cmbes.ca/index.php/proceedings/article/download/160/156

A Biological Approach to Speech Spectrography

The auditory system.

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