Add to ORKGDistributed and parallel processing of big data has been applied in various applications for the past few years. Moreover, huge advancements took place in usability, economic efficiency, and multiplicity of parallel processing systems, with big data analysis and speech recognition research supported by many researchers. In this paper we examined and investigated which parts of speech recognition research may be parallelized and computed using distributed computing platforms. Firstly, we address the case of efficiently computing n-gram statistics on MapReduce platforms to build a language model (LM). Secondly, we show how the Automated Speech Recognition (ASR) tool can work efficiently regarding the speed and fault-tolerance in distributed e...
The automatic recognition of spoken words is increasingly common, for dictaphone applications, telep...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
In this paper, the server based solution of the multi-thread large vocabulary automatic speech recog...
Automatic speech recognition enables a wide range of current and emerging applications such as autom...
Parallel scalability allows an application to efficiently uti-lize an increasing number of processin...
Research in Automatic Speech Recognition (ASR) has been very intense in recent years with focus give...
State-of-the-art speech-recognition systems can successfully perform simple tasks in real-time on mo...
In this paper, we attempt to decompose a state-of-the-art speech recognition system into its compone...
This thesis presents a cloud platform for automatic speech recognition, CloudASR, built on top of Ka...
This thesis presents a fully pipelined and parameterised parallel hardware implementation of a large...
We present a parallel approach for integrating speech and natural language understanding. The method...
We present a parallel approach for integrating speech and natural language understanding. The method...
For years researchers have worked toward finding a way to allow people to talk to machines in the sa...
To achieve improved real-time performance, hardware-based speech recognition systems have emerged in...
UnrestrictedWith wide proliferation of mobile devices and the explosion of new multimedia applicatio...
The automatic recognition of spoken words is increasingly common, for dictaphone applications, telep...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
In this paper, the server based solution of the multi-thread large vocabulary automatic speech recog...
Automatic speech recognition enables a wide range of current and emerging applications such as autom...
Parallel scalability allows an application to efficiently uti-lize an increasing number of processin...
Research in Automatic Speech Recognition (ASR) has been very intense in recent years with focus give...
State-of-the-art speech-recognition systems can successfully perform simple tasks in real-time on mo...
In this paper, we attempt to decompose a state-of-the-art speech recognition system into its compone...
This thesis presents a cloud platform for automatic speech recognition, CloudASR, built on top of Ka...
This thesis presents a fully pipelined and parameterised parallel hardware implementation of a large...
We present a parallel approach for integrating speech and natural language understanding. The method...
We present a parallel approach for integrating speech and natural language understanding. The method...
For years researchers have worked toward finding a way to allow people to talk to machines in the sa...
To achieve improved real-time performance, hardware-based speech recognition systems have emerged in...
UnrestrictedWith wide proliferation of mobile devices and the explosion of new multimedia applicatio...
The automatic recognition of spoken words is increasingly common, for dictaphone applications, telep...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
In this paper, the server based solution of the multi-thread large vocabulary automatic speech recog...