Covariance Matrix Estimation and Classification With Limited Training Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hybrid HMM-NN Architectures for Connected Digit Recognition
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Multilingual Speech Processing
Multilingual Speech Processing
Automatic speech recognition for under-resourced languages: application to Vietnamese language
IEEE Transactions on Audio, Speech, and Language Processing
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The long term goal of our project is the development of robust ASR systems in the Basque context where coexist French, Spanish and Basque (a minority language). The development of ASR systems involves dealing with issues such as Acoustic Phonetic Decoding (APD), Language Modelling (LM) or the development of appropriate Language Resources (LR). Thus, these applications are generally very language-dependent and require very large resources. This work is focused on the selection of appropriate sub-word units with under-resourced and noisy conditions. Nowadays, in particular, the work is oriented to Basque Broadcast News (BN) due to the interest of digital mass-media as the trilingual Infozazpi radio (situated in French Basque Country). Thus, in order to decrease the negative impact that the lack of resources has in this issue we apply several data optimization methodologies based on Matrix Covariance Estimation and Ontology-based approaches.