Multilingual weighted codebooks

In this paper we present an approach for speech recognition of multiple languages with constrained resources on embedded devices. Examples of such systems are navigation systems, mobile phones and MP3 players. Speech recognizers on such systems are typically to-date semi-continuous speech recognizers, which are based on vector quantization. Typical vector quantization algorithms can only generate vector quantization prototypes that are optimal for one language. We hypothesize and provide evidence that a certain fixed vector quantization is responsible for a significant drop of recognition performance when a recognizer is extended to recognize multiple languages at the same time. This paper proposes an algorithm for the construction of Multilingual Weighted Codebooks (MWCs). These MWCs have the advantage that they offer significantly improved performance for the recognition of multiple languages.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Martin Raab, Rainer Gruhn, Elmar Nöth
• Keywords: ICASSP 2008, Multiple Languages, Signal Processing, Vector Quantization, Vector Quantization Algorithms