We present an algorithm for the incremental generation of word graphs. Incremental means that the speech signal is processed left-to-rightby a time synchronous Viterbi algorithm and word hypotheses are generated with some delay to Viterbi decoding. The incrementally generated word hypotheses can be used for early interaction between linguistic analysis and acoustic recognition. Therefore, it is possible to derive acoustic constraints from linguistic restrictions dynamically. 1.

In this paper we report efforts at LIMSI in speaker independent large vocabulary speech recognition in French and in English. The recognizer makes use of continuous density HMM (CDHMM) with Gaussian mixture for acoustic modeling and n-gram statistics estimated on text material for language modeling. Acoustic modeling uses cepstrum-based features, context-dependent phone models (intra and interword), phone duration models, and sex-dependent models. The