Context-dependent units for vocabulary-independent Spanish speech recognition

One of the most important issues in large-vocabulary speech recognition systems is the vocabulary-independence. In order to achieve this goal, modeling of vocabulary words by subwords units is mandatory. This paper studies the use of different subword units, comparing context-independent and context-dependent units (biphones, triphones and artificially generated triphones). From the experimental results we conclude the enormous importance of context dependence units and the good behaviour of biphone units compared to triphones for Spanish speech recognition considering the database limitations and the hardware restrictions in real systems. In order to consider the most important contextual effects in Castilian speech recognition we propose a new and simple approach based on the use of left and right-side biphones. Recognition results of 91.03% correct for vocabulary dependent data (448 surnames), and 89.6% correct for vocabulary independent data (955 surnames), using only 467 senones and 4 mixtures per state, on real telephone speech and speaker independent data are reported