Automatic speech recognition technical for Náhuatl language isolated words

Automatic speech recognition (ASR) represents a great expectative in communications systems where interaction between computers and humans is present. In the last three decades it has been grounded. The use of computer techniques helps people who speak in a native language or with physical limitation to make transactions, leave messages, obtain information, or control some device using voice expressions. This work shows results obtained when using different techniques of ASR into the Náhuatl language. Náhuatl language is a native language spoken in Mexico and is the most important because there are many people speaking it. Náhuatl language has around 49 variants. Preserving language is important because language is the most efficient means of transmitting a culture and it is the owners of that culture who lose the most when the language dies. Mel cepstrum coefficients, vector quantization, and hidden Markov models of continuous density were used. The experiments reported 99% accuracy in ASR on Náhuatl numerals corpus employed. This work represents the first step for implementing an automatic speech recognition translator into Spanish from the Náhuatl language, with closed sentences.