Add to ORKGThis master thesis characterizes the performance and energy bottlenecks of speech recognition systems when running on modern GPU, with the aim of providing useful information for designing future GPU architectures, as well as proposing a GPU configuration more well-suited for speech recognition
In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evalu...
Automatic Speech Recognition (ASR) is becoming increasingly ubiquitous, especially in the mobile seg...
To achieve improved real-time performance, hardware-based speech recognition systems have emerged in...
This master thesis characterizes the performance and energy bottlenecks of speech recognition system...
This paper introduces the use of Graphics Processors Unit (GPU) for computing acoustic likelihoods i...
Automatic speech recognition (ASR) is a very demanding computing task. Much research has been done i...
MSc (Computer Science), North-West University, Mafikeng Campus, 2014In a typical recognition process...
Tématem této diplomové práce je využití grafické karty pro urychlení zpracování řeči. Práce obsahuje...
A speech recognition system can be classified based on two factors: (1) whether the system is speake...
Gaussian Mixture Model (GMM) computations in modern Automatic Speech Recognition systems are known t...
In this paper, we describe an optimized version of a Gaussian-mixture-based acoustic model likelihoo...
In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evalua...
We propose a system architecture for real-time hardware speech recognition on low-cost, power-constr...
Accurate real-time speech recognition is not currently possible in the mobile embedded space where t...
This thesis presents a fully pipelined and parameterised parallel hardware implementation of a large...
In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evalu...
Automatic Speech Recognition (ASR) is becoming increasingly ubiquitous, especially in the mobile seg...
To achieve improved real-time performance, hardware-based speech recognition systems have emerged in...
This master thesis characterizes the performance and energy bottlenecks of speech recognition system...
This paper introduces the use of Graphics Processors Unit (GPU) for computing acoustic likelihoods i...
Automatic speech recognition (ASR) is a very demanding computing task. Much research has been done i...
MSc (Computer Science), North-West University, Mafikeng Campus, 2014In a typical recognition process...
Tématem této diplomové práce je využití grafické karty pro urychlení zpracování řeči. Práce obsahuje...
A speech recognition system can be classified based on two factors: (1) whether the system is speake...
Gaussian Mixture Model (GMM) computations in modern Automatic Speech Recognition systems are known t...
In this paper, we describe an optimized version of a Gaussian-mixture-based acoustic model likelihoo...
In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evalua...
We propose a system architecture for real-time hardware speech recognition on low-cost, power-constr...
Accurate real-time speech recognition is not currently possible in the mobile embedded space where t...
This thesis presents a fully pipelined and parameterised parallel hardware implementation of a large...
In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evalu...
Automatic Speech Recognition (ASR) is becoming increasingly ubiquitous, especially in the mobile seg...
To achieve improved real-time performance, hardware-based speech recognition systems have emerged in...