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Medical – pharmaceutical information system with recognition of Lithuanian voice commands
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This paper presents a Lithuanian voice recognition system of medical – pharmaceutical terms. The system consists of two separate speech recognition modules working in parallel. One recognizer is a proprietary CD-HMM Lithuanian speech recognizer. The second recognizer is a Spanish speech recognizer adapted to recognize Lithuanian voice commands. The outputs of both recognizers are combined by the decision making block yielding the final decision. The decision making block was automatically derived by an induction algorithm that learns a set of symbolic rules. The investigations showed that both recognizers produce uncorrelated outputs and could complement each other. The investigations also showed that Lithuanian speech recognizer achieves higher accuracy (over 96 percent in a speaker independent mode) but the use of the adapted foreign language recognizer allows increase this baseline accuracy even further (over 98 percent in a speaker independent mode for 1000 voice commands). The voice recognition system is in the process of being embedded into several medical information systems which will be used by healthcare practitioners.
Title: Medical – pharmaceutical information system with recognition of Lithuanian voice commands
Description:
This paper presents a Lithuanian voice recognition system of medical – pharmaceutical terms.
The system consists of two separate speech recognition modules working in parallel.
One recognizer is a proprietary CD-HMM Lithuanian speech recognizer.
The second recognizer is a Spanish speech recognizer adapted to recognize Lithuanian voice commands.
The outputs of both recognizers are combined by the decision making block yielding the final decision.
The decision making block was automatically derived by an induction algorithm that learns a set of symbolic rules.
The investigations showed that both recognizers produce uncorrelated outputs and could complement each other.
The investigations also showed that Lithuanian speech recognizer achieves higher accuracy (over 96 percent in a speaker independent mode) but the use of the adapted foreign language recognizer allows increase this baseline accuracy even further (over 98 percent in a speaker independent mode for 1000 voice commands).
The voice recognition system is in the process of being embedded into several medical information systems which will be used by healthcare practitioners.
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