Band-pass filtering of the time sequences of spectral parameters for robust wireless speech recognition

In this paper we address the problem of automatic speech recognition when wireless speech communication systems are involved. In this context, three main sources of distortion should be considered: acoustic environment, speech coding and transmission errors. Whilst the first one has already received a lot of attention, the last two deserve further investigation in our opinion. We have found out that band-pass filtering of the recognition features improves ASR performance when distortions due to these particular communication systems are present. Furthermore, we have evaluated two alternative configurations at different bit error rates (BER) typical of these channels: band-pass filtering the LP-MFCC parameters or a modification of the RASTA-PLP using a sharper low-pass section perform consistently better than LP-MFCC and RASTA-PLP, respectively.Publicad

Recognizing GSM Digital Speech

The Global System for Mobile (GSM) environment encompasses three main problems for automatic speech recognition (ASR) systems: noisy scenarios, source coding distortion, and transmission errors. The first one has already received much attention; however, source coding distortion and transmission errors must be explicitly addressed. In this paper, we propose an alternative front-end for speech recognition over GSM networks. This front-end is specially conceived to be effective against source coding distortion and transmission errors. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bitstream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant advantages. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion as a result of the encoding-decoding process. Second, when transmission errors occur, our front-end becomes more effective since it is not affected by errors in bits allocated to the excitation signal. We have considered the half and the full-rate standard codecs and compared the proposed front-end with the conventional approach in two ASR tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated channel conditions. Furthermore, the disparity increases as the network conditions worsen

Distributed Speech Recognition

This article discusses possibilities of integrating speech technology into wireless technology, allowing voice input for wireless devices. Distributed speech recognition concept and activities related to its standardization are presented. First ETSI DSR MFCC based standard is described. Work on its extension to improve robustness resulting in new standard is also presented

Non-linear echo cancellation - a Bayesian approach

Echo cancellation literature is reviewed, then a Bayesian model is introduced and it is shown how how it can be used to model and fit nonlinear channels. An algorithm for cancellation of echo over a nonlinear channel is developed and tested. It is shown that this nonlinear algorithm converges for both linear and nonlinear channels and is superior to linear echo cancellation for canceling an echo through a nonlinear echo-path channel