Add to ORKGWe present a parallel approach for integrating speech and natural language understanding. The method emphasizes a hierarchically-structured knowledge base and memory-based parsing techniques. Processing is carried out by passing multiple markers in parallel through the knowledge base. Speech-specific problems such as insertion, deletion, substitution, and word boundary detection have been analyzed and their parallel solutions are provided. Results on the SNAP-1 multiprocessor show an 80% sentence recognition rate for the Air Traffic Control (ATC) domain. Furthermore, speed-up of up to 15-fold is obtained from the parallel platform which provides response times of a few seconds per sentence for the ATC domain
State-of-the-art speech-recognition systems can successfully perform simple tasks in real-time on mo...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
The past decade of reseatch in Natural Language Processing has universally recognized that, since na...
We present a parallel approach for integrating speech and natural language understanding. The method...
To reduce the complexity of studying a parallel mechanism for natural language learning and understa...
Automatic speech recognition enables a wide range of current and emerging applications such as autom...
This paper presents a parallel approach for utilizing contextual knowledge to improve spoken languag...
For years researchers have worked toward finding a way to allow people to talk to machines in the sa...
Research in Automatic Speech Recognition (ASR) has been very intense in recent years with focus give...
To communicate with a computer in spoken language is an unattained challenge of Artificial Intellige...
The automatic recognition of spoken words is increasingly common, for dictaphone applications, telep...
Natural Language Processing (NLP)is an important research direction, since it addresses the needs of...
This paper refers to an activity under way at the speech recognition technology level for the develo...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
Distributed and parallel processing of big data has been applied in various applications for the pas...
State-of-the-art speech-recognition systems can successfully perform simple tasks in real-time on mo...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
The past decade of reseatch in Natural Language Processing has universally recognized that, since na...
We present a parallel approach for integrating speech and natural language understanding. The method...
To reduce the complexity of studying a parallel mechanism for natural language learning and understa...
Automatic speech recognition enables a wide range of current and emerging applications such as autom...
This paper presents a parallel approach for utilizing contextual knowledge to improve spoken languag...
For years researchers have worked toward finding a way to allow people to talk to machines in the sa...
Research in Automatic Speech Recognition (ASR) has been very intense in recent years with focus give...
To communicate with a computer in spoken language is an unattained challenge of Artificial Intellige...
The automatic recognition of spoken words is increasingly common, for dictaphone applications, telep...
Natural Language Processing (NLP)is an important research direction, since it addresses the needs of...
This paper refers to an activity under way at the speech recognition technology level for the develo...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
Distributed and parallel processing of big data has been applied in various applications for the pas...
State-of-the-art speech-recognition systems can successfully perform simple tasks in real-time on mo...
The problem of speech recognition is one that lends itself to parallelization. A common method used ...
The past decade of reseatch in Natural Language Processing has universally recognized that, since na...