NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
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ATAL introduced a technique for decomposing speech into phone-length temporal events in terms of overlapping <strong>and</strong><br />
interacting articulatory gestures. This paper reports on simplifications of this technique with applications to acoustic-phonetic<br />
synthesis. Spectral evolution is represented by time-indexed trajectories in the p-dimensional space of Log-Area Ratios {y(sub<br />
i) = Ln ((1+k(sub i))/(1-k(sub i))} where k(sub i) are the reflection coefficients obtained from short-time stationary LPC<br />
analysis. The vocal tract configuration (spectral vector) associated with each interpolation function belongs to a finite set of<br />
articulatory targets (vector quantization code book). A set of speech segments (‘polysons’) has been encoded using this<br />
technique. It includes diphones, demi-syllables, <strong>and</strong> other units that are difficult to segment. Temporal decomposition using<br />
target spectra can break the complex encoding of these segments. In particular, coarticulation effects are analytically explained<br />
<strong>and</strong> modeled. It is demonstrated that these new tools provide an adequate environment in our search for better rules in acoustic<br />
speech synthesis.<br />
Author<br />
Phonetics; Reflectance; Decomposition; Interpolation; Syllables; Speech<br />
20060001663 Thomson SINTRA ASM, France<br />
A Continuous Speech Dialog System for the Oral Control of a Sonar Console<br />
Alinat, Pierre; Gallais, Evelyne; Haton, Jean-Paul; Pierrel, Jean-Marie; Richard, Pascal; IEEE International Conference on<br />
Acoustics, Speech, <strong>and</strong> Signal Processing (ICASSP ‘87); Volume 1; 1987, pp. 10.3.1-10.3.4; In English; See also<br />
20060001583; Copyright; Avail.: Other Sources<br />
We present in this paper an application of a continuous speech underst<strong>and</strong>ing system to the control of a sonar console by<br />
a human operator. This application is really useful since it does correspond to a practical need of the operator who has his eyes<br />
busy looking at the sonar screen. It presents three original features : the acoustic-phonetic decoding part of the system is not<br />
based on a classical phoneme labeling process but it yields for each segment of speech a set of acoustic phonetic labels that<br />
describe this segment very precisely. This phonetic labeling is associated with a special procedure for lexical access; - the<br />
system is actually a man-machine dialog system <strong>and</strong> not only a system capable of underst<strong>and</strong>ing a single sentence as it is often<br />
the case. The history of the dialog is used as a special knowledge source during the underst<strong>and</strong>ing process. This point highly<br />
increases the overall performance of the system ; - the underst<strong>and</strong>ing process, <strong>and</strong> particularly the emission of hypotheses, is<br />
based on the knowledge about the language (lexicon <strong>and</strong> syntax) but also on the context of the dialog ; pragmatic knowledge<br />
is thus intimately associated with the analysis of a sentence. The paper presents the architecture of the system <strong>and</strong> its various<br />
components. It also discusses experimental results obtained in a multispeaker mode.<br />
Author<br />
Sonar; Speech Recognition; Remote Consoles; Phonetics; Systems Engineering<br />
20060001672 American Telephone <strong>and</strong> Telegraph Co., NJ, USA<br />
Continuous Speech Recognition by Means of Acoustic/Phonetic Classification Obtained from a Hidden Markov Model<br />
Levinson, S. E.; IEEE International Conference on Acoustics, Speech, <strong>and</strong> Signal Processing (ICASSP ‘87); Volume 1; 1987,<br />
pp. 3.8.1-3.8.4; In English; See also 20060001583; Copyright; Avail.: Other Sources<br />
This paper describes an experimental continuous speech recognition system comprising procedures for acoustic/phonetic<br />
classification, lexical access <strong>and</strong> sentence retrieval. Speech is assumed to be composed of a small number of phonetic units<br />
which may be identified with the states of a hidden Markov model. The acoustic correlates of the phonetic units are then<br />
characterized by the observable Gaussian process associated with the corresponding state of the underlying Markov chain.<br />
Once the parameters of such a model are determined, a phonetic transcription of an utterance can be obtained by means of<br />
a Viterbi-like algorithm. Given a lexicon in which each entry is orthographically represented in terms of the chosen phonetic<br />
units, a word lattice is produced by a lexical access procedure. Lexical items whose orthography matches subsequences of the<br />
phonetic transcription are sought by means of a hash coding technique <strong>and</strong> their likelihoods are computed directly from the<br />
corresponding interval of acoustic measurements. The recognition process is completed by recovering from the word lattice,<br />
the string of words of maximum likelihood conditioned on the measurements. The desired string is derived by a best-first<br />
search algorithm. In an experimental evaluation of the system, the parameters of an acoustic/phonetic model were estimated<br />
from fluent utterances of 37 seven-digit numbers. A digit recognition rate of 96% was then observed on an independent test<br />
set of 59 utterances of the same form from the same speaker. Half of the observed errors resulted from insertions while<br />
deletions <strong>and</strong> substitutions accounted equally for the other half.<br />
Author<br />
Acoustic Measurement; Speech Recognition; Phonetics; Maximum Likelihood Estimates; Markov Chains; Classifications<br />
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