Recognition performance of the siemens front-end with and without frame dropping on the Aurora 2 database

Abstract Following the objective of the Eurospeech special event,'Noise Robust Recognition', the recognition results of a noiserobust front-end, developed by Siemens, on the Aurora 2 da-tabase [1] are presented in this paper. The front-end wastested with and without a frame dropping algorithm. It isshown that the front-end improves the recognition results inhigh mismatch between training and testing by 43.90% overthe reference front-end and works particularily well in con-ditions with high noise. Furthermore it is shown that theframe dropping mainly increases the performance of the front-end. 1. Introduction The front-end employed is a cepstral analysis scheme withspectral attenuation and spectral subtraction, a channel com-pensation, calculation of the time derivatives, an LDA and aframe dropping algorithm (Figure 1).Details of the front-end can be seen from Table 1. The spe-cific algorithms are shortly described in the following.Parameter settings of the front-endFrame length: 32 msFrame shift: 15 msNumber of samples per frame, NF: 256Preemphasis factor: 0.95Lenght of FFT, FFTL: 256Number of Mel filter banks: 15Number of cepstral coefficients: 12Number of first derivatives: 13Number of second derivatives: 13Size of the feature vector: 24Table 1: Parameter settings of the front-end