- Hua Yu, A. Waibel. 2000. Streamlining the front end of a speech recognizer. Abstract: In this paper we seek to streamline various operations within the front end of a speech recognizer, both to reduce unnecessary computation and to simplify the conceptual framework. First, a novel view of the front end in terms of linear transformations is presented. Then we study the invariance property of recognition performance with respect to linear transformations (LT) at the front end. Analysis reveals that several LT steps can be consolidated into a single LT, which effectively eliminates the Discrete Cosine Transform (DCT) step, part of the traditional MFCC (Mel-Frequency Cepstral Coefﬁcient) front end. Moreover, a highly simpliﬁed, data-driven front-end scheme is proposed as a direct generalization of this idea. The new setup has no Mel-scale ﬁltering, another part of the MFCC front end. Experimental results show a 5% relative improvement on the Broadcast News task.
