Recurrent Neural Network Based Language Modeling in Meeting Recognition

Investigating Bidirectional Recurrent Neural Network Language Models for Speech Recognition

Recurrent neural network language models (RNNLMs) are powerful language modeling techniques. Significant performance improvements have been reported in a range of tasks including speech recognition compared to n-gram language models. Conventional n-gram and neural network language models are trained to predict the probability of the next word given its preceding context history. In contrast, bi...

Speech Emotion Recognition Using Scalogram Based Deep Structure

Speech Emotion Recognition (SER) is an important part of speech-based Human-Computer Interface (HCI) applications. Previous SER methods rely on the extraction of features and training an appropriate classifier. However, most of those features can be affected by emotionally irrelevant factors such as gender, speaking styles and environment. Here, an SER method has been proposed based on a concat...

遞迴式類神經網路語言模型應用額外資訊於語音辨識之研究 (Recurrent Neural Network-based Language Modeling with Extra Information Cues for Speech Recognition) [In Chinese]

RNNLM - Recurrent Neural Network Language Modeling Toolkit

We present a freely available open-source toolkit for training recurrent neural network based language models. It can be easily used to improve existing speech recognition and machine translation systems. Also, it can be used as a baseline for future research of advanced language modeling techniques. In the paper, we discuss optimal parameter selection and different modes of functionality. The ...

Sequence memoizer based language model for Russian speech recognition

In this paper, we propose a novel language model for Russian large vocabulary speech recognition based on sequence memoizer modeling technique. Sequence memoizer is a long span text dependency model and was initially proposed for character language modeling. Here, we use it to build word level language model (LM) in ASR. We compare its performance with recurrent neural network (RNN) LM, which a...