TY - GEN
T1 - Voice translator based on associative memories
AU - Vázquez, Roberto A.
AU - Sossa, Humberto
PY - 2008
Y1 - 2008
N2 - An associative memory is a particular type of neural network for recalling output patterns from input patterns that might be altered by noise. During the last 50 years, several associative models have emerged and they only have been applied to solve problems where input patterns are images. Most of these models have several constraints that limit their applicability in complex problems. Recently in [13] it was introduced a new associative model based on some aspects of the human brain. This model is robust under different type of noises and image transformations, and useful in complex problems such as face and 3d object recognition. In this paper we adopt this model and apply it to problems that not involve images patterns, we applied to speech recognition problems. In this paper it is described a novel application where an associative memory works as a voice translator device performing a speech recognition process. In order to achieve this, the associative memory is trained using a corpus of 40 English words with their corresponding translation to Spanish. Each association used during training phase is composed by a voice signal in English and a voice signal in Spanish. Once trained our English-Spanish translator, when a voice signal in English is used to stimulate the associative memory we expect that the memory recalls the corresponding voice signal in Spanish. In order to test the accuracy of the proposal, a benchmark of 14500 altered versions of the original voice signals were used.
AB - An associative memory is a particular type of neural network for recalling output patterns from input patterns that might be altered by noise. During the last 50 years, several associative models have emerged and they only have been applied to solve problems where input patterns are images. Most of these models have several constraints that limit their applicability in complex problems. Recently in [13] it was introduced a new associative model based on some aspects of the human brain. This model is robust under different type of noises and image transformations, and useful in complex problems such as face and 3d object recognition. In this paper we adopt this model and apply it to problems that not involve images patterns, we applied to speech recognition problems. In this paper it is described a novel application where an associative memory works as a voice translator device performing a speech recognition process. In order to achieve this, the associative memory is trained using a corpus of 40 English words with their corresponding translation to Spanish. Each association used during training phase is composed by a voice signal in English and a voice signal in Spanish. Once trained our English-Spanish translator, when a voice signal in English is used to stimulate the associative memory we expect that the memory recalls the corresponding voice signal in Spanish. In order to test the accuracy of the proposal, a benchmark of 14500 altered versions of the original voice signals were used.
UR - http://www.scopus.com/inward/record.url?scp=55849108218&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-87734-9_39
DO - 10.1007/978-3-540-87734-9_39
M3 - Contribución a la conferencia
SN - 3540877339
SN - 9783540877332
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 341
EP - 350
BT - Advances in Neural Networks - ISNN 2008 - 5th International Symposium on Neural Networks, ISNN 2008, Proceedings
PB - Springer Verlag
T2 - 5th International Symposium on Neural Networks, ISNN 2008
Y2 - 24 September 2008 through 28 September 2008
ER -