RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition

We compare the fast training and decoding speed of RETURNN of attention models for translation, due to fast CUDA LSTM kernels, and a fast pure TensorFlow beam search decoder. We show that a layer-wise pretraining scheme for recurrent attention models gives over 1% BLEU improvement absolute and it allows to train deeper recurrent encoder networks. Promising preliminary results on max. expected BLEU training are presented. We are able to train state-of-the-art models for translation and end-to-end models for speech recognition and show results on WMT 2017 and Switchboard. The flexibility of RETURNN allows a fast research feedback loop to experiment with alternative architectures, and its generality allows to use it on a wide range of applications.Comment: accepted as demo paper on ACL 201

Speech Recognition Using HMM/ANN Hybrid Model

By the analysis on the principle of speech recognition system, a speech recognition system was designed by using LPC2148 as the hardware platform and MATLAB 2012 as the software platform. Speech recognition is an important component of biological identification which is an integrated technology of acoustics, signal processing and artificial intelligence. Recognition systems based on hidden Markov models are effective under particular circumstances, but do suffer from some major limitations that limit applicability of ASR technology in real-world environments. Attempts were made to overcome these limitations with the adoption of artificial neural networks as an alternative paradigm for ASR, but ANNs were unsuccessful in dealing with long time sequences of speech signals. So taking the limitations and advantages of both the systems it was proposed to combine HMM and ANN within a single, hybrid architecture. The goal in hybrid systems for ASR is to take advantage from the properties of both HMM and ANNs, improving flexibility and ASR performance For Speech recognition features from speech sample are extracted & mapping is done using Artificial Neural Networks. Multilayer pattern mapping neural network, which works on the principle of back propagation algorithm is proposed. Finally Speaker Recognition is done using Hidden Markov Model (HMM). The specialty of this model is the flexible and expandable hidden layer for recognition. DOI: 10.17762/ijritcc2321-8169.150613

Modeling Topic and Role Information in Meetings using the Hierarchical Dirichlet Process

Abstract. In this paper, we address the modeling of topic and role information in multiparty meetings, via a nonparametric Bayesian model called the hierarchical Dirichlet process. This model provides a powerful solution to topic modeling and a flexible framework for the incorporation of other cues such as speaker role information. We present our modeling framework for topic and role on the AMI Meeting Corpus, and illustrate the effectiveness of the approach in the context of adapting a baseline language model in a large-vocabulary automatic speech recognition system for multiparty meetings. The adapted LM produces significant improvements in terms of both perplexity and word error rate.

Automatic Home Appliance Switching Using Speech Recognition Software and Embedded System

In most homes, electrical appliances are controlled and operated manually, this could be difficult and challenging to do when tiredness, handicap, morphological variations (height, aging etc.) and inadequate skill stands in the way as impediment. This study aims to implement a better and more flexible means of controlling home appliances by means of an automated switching mechanism using speech recognition technique. Acoustic signals picked by a microphone controlled by a speech recognition application generate digital signals that are passed to a microcontroller, which in turn dispatches commands that operate the relays to which the appliances in the home are connected. The goal of using speech command to automate the switching of home appliances was achieved and proved to be a more convenient means of switching home appliances