Automatic Sentence Generator
AUTOMATIC SENTENCE GENERATOR SYSTEM FOR SPEECH RECOGNITION APPLICATIONS.
José Luciano Maldonado. Universidad de Los Andes, FACES, Núcleo La Liria, edificio G, piso 1, Instituto de Estadística Aplicada y Computación, IEAC, Mérida, Venezuela. luzmalvy@telcel.net.ve maldonaj@faces.ula.ve Abstract. We describe an experimental computer program which can generate sentences
automatically. To do so, models are first created based on contexts of interest. These models incorporate word histories that are detected in a context dependent training set of sentences. Not only will we be able to automatically generate sentences associated with the theme being modeled, but we will also be able to help recognize phrases and sentences. In other words, this is a module which could be part of an automatic speech recognition system, so that proposed recognized word sequences can be validated according to acceptable contexts. The system is adaptive and incremental, since models can be modified with additional training sentences, which would expand a previously established capacity.
Key words: corpus, vocabulary, training, recognition, recognizer, generator, histories, context, decoder.
1.- Introduction. The growing, unstoppable development of very high speed information processing computers with tremendous main memory capacity which we see today leads us to think that it will be possible to design and construct automatic speech recognition systems which can detect and code all the grammatical components of a training corpus. As part of our effort to make a contribution to the fascinating world of Automatic Speech Recognition, we have developed a system composed of a set of computer programs. We have observed that on the basis of a model of a small corpus made up of sentences in a particular context, we can automatically generate a great quantity of grammatically correct sentences with this context. Also, our system can effect a linguistic discrimination to the point of rejecting, as
José Luciano Maldonado. Universidad de Los Andes, FACES, Núcleo La Liria, edificio G, piso 1, Instituto de Estadística Aplicada y Computación, IEAC, Mérida, Venezuela. luzmalvy@telcel.net.ve maldonaj@faces.ula.ve Abstract. We describe an experimental computer program which can generate sentences
automatically. To do so, models are first created based on contexts of interest. These models incorporate word histories that are detected in a context dependent training set of sentences. Not only will we be able to automatically generate sentences associated with the theme being modeled, but we will also be able to help recognize phrases and sentences. In other words, this is a module which could be part of an automatic speech recognition system, so that proposed recognized word sequences can be validated according to acceptable contexts. The system is adaptive and incremental, since models can be modified with additional training sentences, which would expand a previously established capacity.
Key words: corpus, vocabulary, training, recognition, recognizer, generator, histories, context, decoder.
1.- Introduction. The growing, unstoppable development of very high speed information processing computers with tremendous main memory capacity which we see today leads us to think that it will be possible to design and construct automatic speech recognition systems which can detect and code all the grammatical components of a training corpus. As part of our effort to make a contribution to the fascinating world of Automatic Speech Recognition, we have developed a system composed of a set of computer programs. We have observed that on the basis of a model of a small corpus made up of sentences in a particular context, we can automatically generate a great quantity of grammatically correct sentences with this context. Also, our system can effect a linguistic discrimination to the point of rejecting, as
Bibliography: [1] A. Bonafonte and J. Mariño, "Language Modeling using X-Grams", International Conference on Spoken Language Processing, ICSLP-96. [2] J. Deller, J. Proakis and J. Hansen, Discrete-Time Processing of Speech Signals. Macmillan Publishing Company.