Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …

TensorFlow is a machine learning system that operates at large scale and in heterogeneous
environments. Tensor-Flow uses dataflow graphs to represent computation, shared state …

TensorFlow is an interface for expressing machine learning algorithms, and an
implementation for executing such algorithms. A computation expressed using TensorFlow …

In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …

Communication has been an essential part of being human and living in society. There are
several different languages and variations of them, so you can speak English in one place …

Abstract Language Identification (LI) is one of the widely emerging field in the areas of
speech processing to accurately identify the language from the data base based on some …

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently
outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks …

Abstract Language Identification (LID) systems are used to classify the spoken language
from a given audio sample and are typically the first step for many spoken language …

Language identification is critical for many downstream tasks in automatic speech
recognition (ASR), and is beneficial to integrate into multilingual end-to-end ASR as an …

Spoken language identification (LID) is the process of determining and classifying natural
language from a given content and dataset. Data must be processed to extract useful …