-
[show abstract]
[hide abstract]
ABSTRACT: In speech processing the short-time magnitude spectrum is believed to contain most of the information about speech intelligibility and it is normally computed using the short-time Fourier transform over 20-40 ms window duration. In this paper, we investigate the effect of the analysis window duration on speech intelligibility in a systematic way. For this purpose, both subjective and objective experiments are conducted. The subjective experiment is in a form of a consonant recognition task by human listeners, whereas the objective experiment is in a form of an automatic speech recognition (ASR) task. In our experiments various analysis window durations are investigated. For the subjective experiment we construct speech stimuli based purely on the short-time magnitude information. The results of the subjective experiment show that the analysis window duration of 15-35 ms is the optimum choice when speech is reconstructed from the short-time magnitude spectrum. Similar conclusions were made based on the results of the objective (ASR) experiment. The ASR results were found to have statistically significant correlation with the subjective intelligibility results.
Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on; 01/2011
-
[show abstract]
[hide abstract]
ABSTRACT: In this paper we propose two new methods of improving the robustness of Automatic Speaker Identification systems. These methods rely on using long-term information in the speech signal to improve the robustness of the features. The first method involves averaging filterbank parameters from consecutive short-time frames over a longer window. The second method investigates the use of frame lengths longer than generally assumed stationary. We show that these two methods result in an improvement over standard Mel Frequency Cepstral Coefficients in the presence of additive white Gaussian noise in speaker identification applications. Furthermore, additional improvements are observed at mid-range SNR when the proposed methods are used in combination.
Signal Processing and Communication Systems (ICSPCS), 2010 4th International Conference on; 01/2011
-
[show abstract]
[hide abstract]
ABSTRACT: The short-time Fourier transform (STFT) of a speech signal has two components: the short-time magnitude spectrum and the short-time phase spectrum. It is traditionally believed that the short-time magnitude spectrum plays the dominant role for speech perception at small window durations (20-40 ms). However, recent perceptual studies have shown that the short-time phase spectrum can contribute as much to speech intelligibility as the short-time magnitude spectrum. It was observed that the use of the rectangular (non-tapered) analysis window for the computation of the short-time phase spectrum is more advantageous than the use of the Hamming (tapered) analysis window. This paper investigates the effect that the dynamic range of an analysis window has on the intelligibility of speech for phase-only and magnitude-only stimuli. For this purpose, the Chebyshev analysis window with adjustable equi-ripple side-lobes is employed. Two types of magnitude-only stimuli are investigated: random phase and zero phase. It is shown that the intelligibility of the magnitude-only stimuli constructed with zero phase is independent of the dynamic range of the analysis window, while the random phase stimuli are intelligible only for analysis windows with high dynamic range. This study also shows that for low dynamic range analysis windows, the short-time phase spectrum at small window durations (20-40 ms) contributes as much as to speech intelligibility as the short-time magnitude spectrum
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on; 05/2007 · 4.63 Impact Factor
