21,410 research outputs found
Real-time interactive speech technology at Threshold Technology, Incorporated
Basic real-time isolated-word recognition techniques are reviewed. Industrial applications of voice technology are described in chronological order of their development. Future research efforts are also discussed
Integrated speech and morphological processing in a connectionist continuous speech understanding for Korean
A new tightly coupled speech and natural language integration model is
presented for a TDNN-based continuous possibly large vocabulary speech
recognition system for Korean. Unlike popular n-best techniques developed for
integrating mainly HMM-based speech recognition and natural language processing
in a {\em word level}, which is obviously inadequate for morphologically
complex agglutinative languages, our model constructs a spoken language system
based on a {\em morpheme-level} speech and language integration. With this
integration scheme, the spoken Korean processing engine (SKOPE) is designed and
implemented using a TDNN-based diphone recognition module integrated with a
Viterbi-based lexical decoding and symbolic phonological/morphological
co-analysis. Our experiment results show that the speaker-dependent continuous
{\em eojeol} (Korean word) recognition and integrated morphological analysis
can be achieved with over 80.6% success rate directly from speech inputs for
the middle-level vocabularies.Comment: latex source with a4 style, 15 pages, to be published in computer
processing of oriental language journa
Study to determine potential flight applications and human factors design guidelines for voice recognition and synthesis systems
A study was conducted to determine potential commercial aircraft flight deck applications and implementation guidelines for voice recognition and synthesis. At first, a survey of voice recognition and synthesis technology was undertaken to develop a working knowledge base. Then, numerous potential aircraft and simulator flight deck voice applications were identified and each proposed application was rated on a number of criteria in order to achieve an overall payoff rating. The potential voice recognition applications fell into five general categories: programming, interrogation, data entry, switch and mode selection, and continuous/time-critical action control. The ratings of the first three categories showed the most promise of being beneficial to flight deck operations. Possible applications of voice synthesis systems were categorized as automatic or pilot selectable and many were rated as being potentially beneficial. In addition, voice system implementation guidelines and pertinent performance criteria are proposed. Finally, the findings of this study are compared with those made in a recent NASA study of a 1995 transport concept
Multi-user real time word recognition system
Technological accomplishments in speech recognition systems are presented. A discrete word recognition system which contains an audio spectrum analyzer is described in detail
New Method for Optimization of License Plate Recognition system with Use of Edge Detection and Connected Component
License Plate recognition plays an important role on the traffic monitoring
and parking management systems. In this paper, a fast and real time method has
been proposed which has an appropriate application to find tilt and poor
quality plates. In the proposed method, at the beginning, the image is
converted into binary mode using adaptive threshold. Then, by using some edge
detection and morphology operations, plate number location has been specified.
Finally, if the plat has tilt, its tilt is removed away. This method has been
tested on another paper data set that has different images of the background,
considering distance, and angel of view so that the correct extraction rate of
plate reached at 98.66%.Comment: 3rd IEEE International Conference on Computer and Knowledge
Engineering (ICCKE 2013), October 31 & November 1, 2013, Ferdowsi Universit
Mashha
Automatic speech recognition research at NASA-Ames Research Center
A trainable acoustic pattern recognizer manufactured by Scope Electronics is presented. The voice command system VCS encodes speech by sampling 16 bandpass filters with center frequencies in the range from 200 to 5000 Hz. Variations in speaking rate are compensated for by a compression algorithm that subdivides each utterance into eight subintervals in such a way that the amount of spectral change within each subinterval is the same. The recorded filter values within each subinterval are then reduced to a 15-bit representation, giving a 120-bit encoding for each utterance. The VCS incorporates a simple recognition algorithm that utilizes five training samples of each word in a vocabulary of up to 24 words. The recognition rate of approximately 85 percent correct for untrained speakers and 94 percent correct for trained speakers was not considered adequate for flight systems use. Therefore, the built-in recognition algorithm was disabled, and the VCS was modified to transmit 120-bit encodings to an external computer for recognition
An acoustic-phonetic approach in automatic Arabic speech recognition
In a large vocabulary speech recognition system the broad phonetic classification
technique is used instead of detailed phonetic analysis to overcome the variability in the
acoustic realisation of utterances. The broad phonetic description of a word is used as a
means of lexical access, where the lexicon is structured into sets of words sharing the
same broad phonetic labelling.
This approach has been applied to a large vocabulary isolated word Arabic speech
recognition system. Statistical studies have been carried out on 10,000 Arabic words
(converted to phonemic form) involving different combinations of broad phonetic
classes. Some particular features of the Arabic language have been exploited. The results
show that vowels represent about 43% of the total number of phonemes. They also show
that about 38% of the words can uniquely be represented at this level by using eight
broad phonetic classes. When introducing detailed vowel identification the percentage of
uniquely specified words rises to 83%. These results suggest that a fully detailed
phonetic analysis of the speech signal is perhaps unnecessary.
In the adopted word recognition model, the consonants are classified into four broad
phonetic classes, while the vowels are described by their phonemic form. A set of 100
words uttered by several speakers has been used to test the performance of the
implemented approach.
In the implemented recognition model, three procedures have been developed, namely
voiced-unvoiced-silence segmentation, vowel detection and identification, and automatic
spectral transition detection between phonemes within a word. The accuracy of both the
V-UV-S and vowel recognition procedures is almost perfect. A broad phonetic
segmentation procedure has been implemented, which exploits information from the
above mentioned three procedures. Simple phonological constraints have been used to
improve the accuracy of the segmentation process. The resultant sequence of labels are
used for lexical access to retrieve the word or a small set of words sharing the same broad
phonetic labelling. For the case of having more than one word-candidates, a verification
procedure is used to choose the most likely one
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