A novel framework for noise robust ASR using cochlear implant-like spectrally reduced speech

Abstract

We propose a novel framework for noise robust automatic speech recognition (ASR) based on cochlear implant-like spectrally reduced speech (SRS). Two experimental protocols (EPs) are proposed in order to clarify the advantage of using SRS for noise robust ASR. These two EPs assess the SRS in both the training and testing environments. Speech enhancement was used in one of two EPs to improve the quality of testing speech. In training, SRS is synthesized from original clean speech whereas in testing, SRS is synthesized directly from noisy speech or from enhanced speech signals. The synthesized SRS is recognized with the ASR systems trained on SRS signals, with the same synthesis parameters. Experiments show that the ASR results, in terms of word accuracy, calculated with ASR systems using SRS, are significantly improved compared to the baseline non-SRS ASR systems. We propose also a measure of the training and testing mismatch based on the Kullback-Leibler divergence. The numerical results show that using the SRS in ASR systems helps in reducing significantly the training and testing mismatch due to environmental noise. The training of the HMM-based ASR systems and the recognition tests were performed by using the HTK toolkit and the Aurora 2 speech database.

Acoustic Simulations of Cochlear Implants in Human and Machine Hearing Research

“…This system is be used to recognize the SRS which is synthesized from noisy contaminated speech signals. Experimental results show that the use of SRS helps in improving significantly the ASR performance in the recognition of noisy speech (Do et al, 2012).…”

“…In addition, the fact that cochlear implant-like SRS is synthesized from speech temporal envelopes, only, might help in reducing ASR irrelevant spectral information due to environment. In (Do et al, 2012), we perform the ASR experiments with the noise contaminated speech signal. The SRS are used in both training and testing conditions.…”

“…Conventional as well as recently proposed synthesis algorithms have been used to synthesize the SRS signals Shannon et al, 1995). These novel applications show that the acoustic simulation of cochlear implant is an important tool, not only for cochlear implant research but also for other hearing-related applications, namely noise robust ASR (Do et al, 2012). …”

“…In this novel framework, cochlear implant-like SRS is used in both the training and testing conditions. Experiments show that the (automatic) recognition results are significantly improved, compared to the baseline system which does not employ the SRS (Do et al, 2012). Fig.…”

“…for noise robust ASR, using cochlear implant-like SRS, has been proposed in (Do et al, 2012). In this novel framework, cochlear implant-like SRS is used in both the training and testing conditions.…”