Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition

Articulatory Feature based Multilingual MLPs for Low-Resource Speech Recognition

Large vocabulary continuous speech recognition is particularly difficult for low-resource languages. In the scenario we focus on here is that there is a very limited amount of acoustic training data in the target language, but more plentiful data in other languages. In our approach, we investigate approaches based on Automatic Speech Attribute Transcription (ASAT) framework, and train universal...

Multilingual Data Selection for Low Resource Speech Recognition

Feature representations extracted from deep neural networkbased multilingual frontends provide significant improvements to speech recognition systems in low resource settings. To effectively train these frontends, we introduce a data selection technique that discovers language groups from an available set of training languages. This data selection method reduces the required amount of training ...

Automatic Speech Recognition for Low-resource Languages and Accents Using Multilingual and Crosslingual Information

Multilingual Recurrent Neural Networks with Residual Learning for Low-Resource Speech Recognition

The shared-hidden-layer multilingual deep neural network (SHL-MDNN), in which the hidden layers of feed-forward deep neural network (DNN) are shared across multiple languages while the softmax layers are language dependent, has been shown to be effective on acoustic modeling of multilingual low-resource speech recognition. In this paper, we propose that the shared-hidden-layer with Long Short-T...

A comparative study of BNF and DNN multilingual training on cross-lingual low-resource speech recognition

This paper presents a comparative study of bottle-neck feature (BNF) and Deep Neural Network (DNN) multilingual training for low-resource language speech recognition. Besides, we also compared the system performances after fine-tuning. The evaluation was conducted on the IARPA Babel data. The source languages are Cantonese, Pashto, Tagalog, and Turkish, while the target languages are Vietnamese...