Isolated Automatic Speech Recognition of Quechua Numbers using MFCC, DTW and KNN

The Automatic Speech (ASR) area is defined as the transformation of acoustic signals into string words. This area has been being developed for many year facilitating the lives of people so it was implemented in several languages. However, the development of ASR in some languages with few database resources but with a large population speaking these languages is very low. The development of ASR in Quechua language is almost null which leads culture and population isolation from technology and information. In this work an ASR system of isolated Quechua numbers is developed where Mel-Frequency Cepstral Coefficients (MFCC), Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) methods are implemented using a database composed by recorded audio numbers from one to ten in Quechua. The recorded audios to feed the data base were uttered by natives man and women speakers of Quechua. The recognition accuracy reached in this research work was 91.1%.

@article{Chuctaya2018,
  title     = {Isolated Automatic Speech Recognition of Quechua Numbers using MFCC, DTW and KNN},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {10},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Hernan Faustino Chacca Chuctaya and Rolfy Nixon Montufar Mercado and Jeyson Jesus Gonzales Gaona},
  doi       = {10.14569/IJACSA.2018.091003},
  url       = {https://doi.org/10.14569/IJACSA.2018.091003}
}