We present a method to use speech data from multiple languages to enhance the performance of a flexible vocabulary command word recognizer which is trained using a small amount of speech data of the target language. We develop data-driven approaches for identification of multilingual phoneme units and mapping of these units to the target language phonemes, and evaluate them against the knowledg...

Semantic transfer is an important problem of the language understanding (LU), which is about how the recognition pattern of a semantic concept benefits other associated concepts. In this paper, we propose a new semantic representation based on combinatory concepts. Semantic slot is represented as a composition of different atomic concepts in different semantic dimensions. Specifically, we propo...

second language acquisition (sla) always happens when the learners live and have contact with the native speakers of a second language. although this study investigates learning english by ten native children of farsi, the authors try to simulate the second language acquisition environment. the research deals with the initial state and further development in the child second language learning o...

We present a new dependency parsing method for Korean applying cross-lingual transfer learning and domain adaptation techniques. Unlike existing transfer learning methods relying on aligned corpora or bilingual lexicons, we propose a feature transfer learning method with minimal supervision, which adapts an existing parser to the target language by transferring the features for the source langu...

This article explores the properties of ecopoetry that have to do with realisation we are not merely external observers but active and intrinsic participants within biosphere. The type ecopoetics I am advocating takes a subjective stance experience: it begins from individual consciousness is rooted in sensory perception. Reference world through this evokes tone or mood, “atmosphere” between env...

In this paper, we propose an efficient transfer leaning methods for training a personalized language model using a recurrent neural network with long short-term memory architecture. With our proposed fast transfer learning schemes, a general language model is updated to a personalized language model with a small amount of user data and a limited computing resource. These methods are especially ...

This paper describes a novel approach to handling translation divergences in a Generation-Heavy Hybrid Machine Translation (GHMT) system. The translation divergence problem is usually reserved for Transfer and Interlingual MT because it requires a large combination of complex lexical and structural mappings. A major requirement of these approaches is the accessibility of large amounts of explic...