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Speech segmentation without speech recognition
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2003In this paper, we presented a semantic speech segmentation approach, in particular sentence segmentation, without speech recognition. In order to get phoneme level information without word recognition information, a novel vowel/consonant/pause (V/C/P) classification is proposed.
Hong-Jiang Zhang, Dong Wang, Lie Lu
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2008
This chapter gives an overview of the main architectures for enabling speech recognition on embedded devices. Starting with a short overview of speech recognition; an overview of the main challenges for the use on embedded devices is given. Each of the architectures has its own characteristic problems and features.
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This chapter gives an overview of the main architectures for enabling speech recognition on embedded devices. Starting with a short overview of speech recognition; an overview of the main challenges for the use on embedded devices is given. Each of the architectures has its own characteristic problems and features.
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Microphones for speech and speech recognition
The Journal of the Acoustical Society of America, 2004Automatic speech recognition (ASR) requires about a 15- to 20-dB signal-to-noise ratio (S/N) for high accuracy even for small vocabulary systems. This S/N is generally achievable using a telephone handset in normal office or home environments. In the early 1990s ATT and the regional telephone companies began using speaker-independent ASR to replace ...
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A Neural Ensemble For Speech Recognition
1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96, 2005Automatic speech recognition is a severe application for neural networks. An ensemble of more neural networks can be the keystone to increase the performance of the recognizer. Different techniques to pre-process the vocal signal are also shown. This approach is used to implement a “viva voice” recognizer for a car phone.
M. Costa +3 more
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Speech recognition and speech synthesis
Euromicro Newsletter, 1979Abstract Speech synthesis and speech recognition are still in the experimental stage. Much remains to be done in this field, but looking at the ever growing amount of people on this subject the “pergect” speech synthesizer featuring low cost and high performance is to be expected soon.
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Speech recognition based on speech units
European Conference on Speech Technology, 1987In a classical quantization system, each vector is represented by the nearest centroid; two vectors belonging to the same class are then indistinguishable. In order to mitigate this situation, we take into account the two nearest neighbours and define a “belonging degree” calculated from the distances between the vector and the two centroids.
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The Journal of the Acoustical Society of America, 1990
Smoothed frame labeling associates phonetic frame labels with a given speech frame as a function of (a) the closeness with which the given frame compares to each of a plurality of acoustic models, (b) which frame labels correspond with a neighboring frame, and (c) transition probabilities which indicate, for the frame labels associated with the ...
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Smoothed frame labeling associates phonetic frame labels with a given speech frame as a function of (a) the closeness with which the given frame compares to each of a plurality of acoustic models, (b) which frame labels correspond with a neighboring frame, and (c) transition probabilities which indicate, for the frame labels associated with the ...
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Speech perception as pattern recognition
The Journal of the Acoustical Society of America, 1995This work provides theoretical and empirical arguments in favor of an approach to phonetics that is called double-weak. It is so called because it assumes relatively weak constraints both on the articulatory gestures and on the auditory patterns that map phonological elements.
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2018
This chapter talks about the impact of AI on speech recognition and conversational interfaces. It will touch upon bots classification, main models used and developed in speech recognition as well as a market classification where major start-up players are identified.
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This chapter talks about the impact of AI on speech recognition and conversational interfaces. It will touch upon bots classification, main models used and developed in speech recognition as well as a market classification where major start-up players are identified.
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Speech Recognition and Understanding
1976Speech is man’s most natural channel of communication, so it is only natural that it should be the subject of much work in pattern recognition. Recognizing speech is difficult, for the nature of the speech communication process is such that the resulting acoustic signal is highly encoded and full of contextual dependencies.
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