Analysis of Factors Influencing Accuracy of Speech Recognition
G. Čeidaitė,Laimutis Telksnys +1 more
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The analysis of experimental results proved that the biggest influence on recognition accuracy has environments’ in which speech commands’ recognition are used and size set of etalons of speech commands used for training.Abstract:
Factors influencing accuracy of speech recognitions is investigated The main attention was given to environment, training conditions and features The results of the influence of the factors to the accuracy of speech recognition are presented The analysis of experimental results proved that the biggest influence on recognition accuracy has environments’ in which speech commands’ recognition are used and size set of etalons of speech commands used for trainingread more
Citations
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References
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Developments and directions in speech recognition and understanding, Part 1 [DSP Education]
J. Baker,Li Deng,James Glass,Sanjeev Khudanpur,Chin-Hui Lee,Nelson Morgan,Douglas O'Shaughnessy +6 more
TL;DR: The working group producing this article was charged to elicit from the human language technology community a set of well-considered directions or rich areas for future research that could lead to major paradigm shifts in the field of automatic speech recognition (ASR) and understanding.
Proceedings ArticleDOI
Microphone array speech recognition: experiments on overlapping speech in meetings
Darren Moore,Iain McCowan +1 more
TL;DR: This paper investigates the use of microphone arrays to acquire and recognise speech in meetings, and proposes an appropriate microphone array geometry and improved processing technique for this scenario, paying particular attention to speaker separation.
Journal ArticleDOI
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J. Baker,Li Deng,Sanjeev Khudanpur,Chin-Hui Lee,James Glass,Nelson Morgan,Douglas O'Shaughnessy +6 more
TL;DR: This article is the second part of an updated version of the "MINDS 2006-2007 Report of the Speech Understanding Working Group," one of five reports emanating from two workshops entitled "Meeting of the MINDS: Future Directions for Human Language Technology," sponsored by the U.S. Disruptive Technology Office (DTO).
Proceedings ArticleDOI
Robust speech recognition using near-field superdirective beamforming with post-filtering
Iain McCowan,C. Marro,L. Mauuary +2 more
TL;DR: The array is shown to have a marked effect on the recognition results in a high noise office environment, particularly where there is a high level of undesired speech.
Proceedings ArticleDOI
Influence of background noise and microphone on the performance of the IBM Tangora speech recognition system
TL;DR: It was found that microphone characteristics had a significant impact on the robustness of the Tangora system, and controlled contamination of the quiet training data with ambient noise improved the noise immunity of the recognizer.