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1
Subword-based approaches for spoken document retrieval
In: Speech communication. - Amsterdam [u.a.] : Elsevier 32 (2000) 3, 157-186
OLC Linguistik
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2
Subword-based approaches for spoken document retrieval
In: Speech communication. - Amsterdam [u.a.] : Elsevier 32 (2000) 3, 157-186
BLLDB
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3
Segment-based automatic language identification
In: Acoustical Society of America. The journal of the Acoustical Society of America. - Melville, NY : AIP 101 (1997) 4, 2323-2331
BLLDB
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4
Phonological Parsing for Bi-directional Letter-to-Sound/Sound-to-Letter Generation
In: DTIC (1994)
BASE
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5
TIMIT Acoustic-Phonetic Continuous Speech Corpus
Garofolo, John S.; Lamel, Lori; Fisher, William. - Philadelphia, PA : Linguistic Data Consortium, 1993
MPI für Psycholinguistik
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6
From signals to symbols to meaning (incl. report on the paper) : on machine understanding of spoken language
In: ICPhS <12, 1991, Aix-en-Provence>. Proceedings of the XIIth International Congress of Phonetic Sciences ; 1. Plenary and semi-plenary sessions. - Aix-en-Provence : Univ. de Provence, Service de Publ. (1991), 74-86
BLLDB
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7
Collection of Spontaneous Speech for the ATIS Domain and Comparative Analyses of Data Collected at MIT and TI
In: DTIC (1991)
BASE
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8
Signal Representation, Attribute Extraction and, the Use of Distinctive Features for Phonetic Classification
In: DTIC (1991)
Abstract: The study reported in this paper addresses three issues related to phonetic classification: 1) whether it is important to choose an appropriate signal representation, 2) whether there are any advantages in extracting acoustic attributes over directly using the spectral information, and 3) whether it is advantageous to introduce an intermediate set of linguistic units, i.e. distinctive features. To restrict the scope of our study, we focused on 16 vowels in American English, and investigated classification performance using an artificial neural network with nearly 22,000 vowels tokens from 550 speakers excised from the TIMIT corpus. Our results indicate that 1) the combined outputs of Seneff's auditory model outperforms five other representations with both undegraded and noisy speech, 2) acoustic attributes give similar performance to raw spectral information, but at potentially considerable computational savings, and 3) the distinctive feature representation gives similar performance to direct vowel classification, but potentially offers a more flexible mechanism for describing context dependency. ; Supported in part by DARPA.
Keyword: *INFORMATION RETRIEVAL; *PHONETICS; CLASSIFICATION; COMPUTATIONS; ENGLISH LANGUAGE; HEARING; Information Science; Linguistics; MODELS; NEURAL NETS; SIGNALS; SPECTRA; SPEECH RECOGNITION; Voice Communications; VOWELS
URL: http://www.dtic.mil/docs/citations/ADA458588
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA458588
BASE
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9
Interactive Problem Solving and Dialogue in the ATIS Domain
In: DTIC (1991)
BASE
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10
Knowledge-based approaches
Querre, M. (Mitarb.); Erman, Lee D. (Mitarb.); Lesser, Victor R. (Mitarb.)...
In: Readings in speech recognition. - San Mateo, Calif. : Kaufmann (1990), 197-262
BLLDB
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11
Speech Communication
Lane, Harlan L.; Holmberg, Eva B.; Ringo, Carol C.. - : Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), 1990
BASE
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12
Speech Communication
Sulter, Arend; Espy-Wilson, Carol Y.; Keyser, Samuel J.. - : Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), 1989
BASE
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13
Speech Database Development
In: DTIC AND NTIS (1988)
BASE
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14
Speech Recognition: Acoustic-Phonetic Knowledge Acquisition and Representation
In: DTIC AND NTIS (1988)
BASE
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15
Speech Communication
Stevens, Kenneth N.; Allen, Jonathan; Halle, Morris. - : Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), 1987
BASE
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16
Speech Communication
Stevens, Kenneth N.; Allen, Jonathan; Halle, Morris. - : Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), 1987
BASE
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17
Speech Recognition: Acoustic-Phonetic Knowledge Acquisition and Representation.
In: DTIC AND NTIS (1987)
BASE
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18
Speech Recognition: Acoustic-Phonetic Knowledge Acquisition and Representation.
In: DTIC AND NTIS (1987)
BASE
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19
Performing fine phonetic distinctions : templates versus features
In: Invariance and variability in speech processes. - Hillsdale, N.J. [u.a.] : Erlbaum Assoc. (1986), 325-345
BLLDB
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20
Speech Communication
Stevens, Kenneth N.; Klatt, Dennis H.; Perkell, Joseph S.. - : Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT), 1986
BASE
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