Title
Low-Resource Language Recognition Using A Fusion Of Phoneme Posteriorgram Counts, Acoustic And Glottal-Based I-Vectors
Abstract
This paper presents a description of our system for the Albayzin 2012 LRE competition. One of the main characteristics of this evaluation was the reduced number of available files for training the system, especially for the empty condition where no training data set was provided but only a development set. In addition, the whole database was created from online videos and around one third of the training data was labeled as noisy files. Our primary system was the fusion of three different i-vector based systems: one acoustic system based on MFCCs, a phonotactic system using trigrams of phone-posteriorgram counts, and another acoustic system based on RPLPs that improved robustness against noise. A contrastive system that included new features based on the glottal source was also presented. Official and postevaluation results for all the conditions using the proposed metrics for the evaluation and the Cavg metric are presented in the paper.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6638989
2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
LID system, noise robustness, scarce data, posteriorgram counts, i-vectors
Training set,Phonotactics,Computer science,Trigram,Fusion,Speech recognition,Robustness (computer science),Language recognition
Conference
ISSN
Citations 
PageRank 
1520-6149
3
0.44
References 
Authors
5
4
Name
Order
Citations
PageRank
Luis Fernando D'Haro118125.97
Ricardo De Córdoba214225.58
Miguel Ánguel Caraballo330.78
José Manuel Pardo415230.36