Search Results - "Lennig, M."

Refine Results
  1. 1
  2. 2

    Putting speech recognition to work in the telephone network by Lennig, M.

    Published in Computer (Long Beach, Calif.) (01-08-1990)
    “…The use of speaker-independent speech recognition in the development of Northern Telecom's automated alternate billing service (AABS) for collect calls,…”
    Get full text
    Journal Article
  3. 3

    Phonemic hidden Markov models with continuous mixture output densities for large vocabulary word recognition by Deng, L., Kenny, P., Lennig, M., Gupta, V., Seitz, F., Mermelstein, P.

    Published in IEEE transactions on signal processing (01-07-1991)
    “…The authors demonstrate the effectiveness of phonemic hidden Markov models with Gaussian mixture output densities (mixture HMMs) for speaker-dependent…”
    Get full text
    Journal Article
  4. 4

    Modeling microsegments of stop consonants in a hidden markov model based word recognizer by DENG, L, LENNIG, M, MERMELSTEIN, P

    “…The motivation of this study is the poor performance of speech recognizers on the stop consonants. To overcome this weakness, word initial and word final stop…”
    Get full text
    Journal Article
  5. 5

    Modeling acoustic transitions in speech by state-interpolation hidden Markov models by Deng, L., Kenny, P., Lennig, M., Mermelstein, P.

    Published in IEEE transactions on signal processing (01-02-1992)
    “…The authors present a new type of hidden Markov model (HMM) for vowel-to-consonant (VC) and consonant-to-vowel (CV) transitions based on the locus theory of…”
    Get full text
    Journal Article
  6. 6

    Use of vowel duration information in a large vocabulary word recognizer by DENG, L, LENNIG, M, MERMELSTEIN, P

    “…In this paper, a method is developed to employ vowel duration properties in a hidden Markov model (HMM)-based large vocabulary speaker trained recognition…”
    Get full text
    Journal Article
  7. 7

    Fast search strategy in a large vocabulary word recognizer by GUPTA, V. N, LENNIG, M, MERMELSTEIN, P

    “…In this article, a fast search algorithm is presented for generating word hypotheses for a 75 000-word vocabulary, speaker-trained, isolated word recognizer…”
    Get full text
    Journal Article
  8. 8

    Speaker adaptation in a large-vocabulary Gaussian HMM recognizer by Kenny, P., Lennig, M., Mermelstein, P.

    “…The problem of using a small amount of speech data to adapt a set of Gaussian HMMs (hidden Markov models) that have been trained on one speaker to recognize…”
    Get full text
    Journal Article
  9. 9

    A new fast match for very large vocabulary continuous speech recognition by Kenny, P., Labute, P., Li, Z., Hollan, R., Lennig, M., O'Shaughnessy, D.

    “…A novel fast match for very large vocabulary continuous speech recognition in which phonetic transcriptions are scored at a cost of one floating-point…”
    Get full text
    Conference Proceeding
  10. 10

    A linear predictive HMM for vector-valued observations with applications to speech recognition by Kenny, P., Lennig, M., Mermelstein, P.

    “…The authors describe a new type of Markov model developed to account for the correlations between successive frames of a speech signal. The idea is to treat…”
    Get full text
    Journal Article
  11. 11

    Hybrid segmental-LVQ/HMM for large vocabulary speech recognition by Cheng, Y.M., O'Shaughnessy, D., Gupta, V., Kenny, P., Lennig, M., Mermelstein, P., Parthasarathy, S.

    “…The authors have assessed the possibility of modeling phone trajectories to accomplish speech recognition. This approach has been considered as one of the ways…”
    Get full text
    Conference Proceeding
  12. 12

    Using phoneme duration and energy contour information to improve large vocabulary isolated-word recognition by Gupta, V.N., Lennig, M., Mermelstein, P., Kenny, P., Seitz, F., O'Shaughnessy, D.

    “…Minimum duration constraints and energy thresholds for phonemes were used to increase the recognition accuracy of an 86000-word speaker-trained isolated word…”
    Get full text
    Conference Proceeding
  13. 13

    A-admissible heuristics for rapid lexical access by Kenny, P., Hollan, R., Gupta, V.N., Lennig, M., Mermelstein, P., O'Shaughnessy, D.

    “…A new class of A* algorithms for Viterbi phonetic decoding subject to lexical constraints is presented. This type of algorithm can be made to run substantially…”
    Get full text
    Journal Article
  14. 14

    Automation of alternate billed calls using speech recognition by Murphy, M., Bielby, G., Roe, B., Read, K., O'Gorman, A., Lennig, M.

    Published in IEEE communications magazine (01-01-1991)
    “…Alternate billed calls (collect, calling-card, bill-to-third-party), which represent close to 50% of the toll and assist traffic in North America, requiring…”
    Get full text
    Magazine Article
  15. 15

    Directory assistance automation in Bell Canada: Trial results by Lennig, Matthew, Bielby, Greg, Massicotte, Julie

    Published in Speech communication (01-11-1995)
    “…Speech recognition was used to automate directory assistance in a 6-month trial with Bell Canada's public customers. The bilingual application gave the caller…”
    Get full text
    Journal Article Conference Proceeding
  16. 16

    Experiments on speaker-independent recognition of hand-segmented French vowels by Lennig, M.

    “…This paper addresses the problem of recognizing hand-segmented vowel phonemes in isolated words pronounced by different speakers. Overcoming variation in the…”
    Get full text
    Conference Proceeding
  17. 17

    Language modeling for very-large-vocabulary speech recognition by O'Shaughnessy, D., Gupta, V., Lennig, M., Seitz, F., Mermelstein, P.

    “…Virtually all recognition systems, both research and commercial, place severe limits on the vocabulary and syntactic structures a speaker may use. This…”
    Get full text
    Journal Article
  18. 18

    Intonation in text-to-speech synthesis: evaluation of algorithms by AKERS, G, LENNIG, M

    “…Two algorithms, termed schematic and naturalistic, for generating intonation contours in an English text-to-speech system are compared by eliciting preference…”
    Get full text
    Journal Article
  19. 19

    Acoustic recognition component of an 86000-word speech recognizer by Deng, L., Gupta, V., Lennig, M., Kenny, P., Mermelstein, P.

    “…Recent results obtained with a hidden Markov model (HMM)-based acoustic recognizer using a virtually unlimited vocabulary (86000 words) to perform…”
    Get full text
    Conference Proceeding
  20. 20

    A locus model of coarticulation in an HMM speech recognizer by Deng, L., Kenny, P., Lennig, M., Gupta, V., Mermelstein, P.

    “…A novel type of hidden Markov model (HMM) has been developed to account explicitly for the context-dependent vowel acoustic transitions in consonant-vowel and…”
    Get full text
    Conference Proceeding