GIOL I5/08(2006.01) In some implementations, data that indicates multiple can GIOL
15/18(2013.01) didate transcriptions for an utterance is received. For each of GIOL …

We present a novel approach for improving the performance of an End-to-End speech
recognition system for the Gujarati language. We follow a deep learning-based approach …

We propose a large margin criterion for training neural language models. Conventionally,
neural language models are trained by minimizing perplexity (PPL) on grammatical …

We focus on the problem of language modeling for code-switched language, in the context
of automatic speech recognition (ASR). Language modeling for code-switched language is …

In a modern spoken language understanding (SLU) system, the natural language
understanding (NLU) module takes interpretations of a speech from the automatic speech …

The recently introduced second CHiME challenge is a difficult two-microphone speech
recognition task with non-stationary interference. Current approaches in the source …

A recurrent neural network language model (RNN-LM) can use a long word context more
than can an n-gram language model, and its effective has recently been shown in its …

We propose a simple yet effective method for improving speech recognition by reranking the
N-best speech recognition hypotheses using search results. We model N-best reranking as …

Recurrent neural networks have become increasingly popular for the task of language
modeling achieving impressive gains in state-of-the-art speech recognition and natural …

We report two tools to conduct psycholinguistic experiments on Turkish words. KelimetriK
allows experimenters to choose words based on desired orthographic scores of word …