ANTONIO MIGUEL PEINADO HERREROS-rekin lankidetzan egindako argitalpenak (12)

2015

  1. Minimum classification error transformations for improving speech recognition systems

    European Signal Processing Conference

2005

  1. Histogram equalization of speech representation for robust speech recognition

    IEEE Transactions on Speech and Audio Processing, Vol. 13, Núm. 3, pp. 355-366

2003

  1. HMM-based channel error mitigation and its application to distributed speech recognition

    Speech Communication, Vol. 41, Núm. 4, pp. 549-561

2002

  1. Discriminative feature weighting for HMM-based continuous speech recognizers

    Speech Communication, Vol. 38, Núm. 3-4, pp. 267-286

  2. Non-linear transformations of the feature space for robust speech recognition

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

2001

  1. Joint source-channel coding for low bit-rate coding of lsp parameters

    EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology

  2. Model-based compensation of the additive noise for continuous speech recognition. Experiments using the AURORA II database and tasks

    EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology

1997

  1. A low-delay transform domain approach to trellis coded quantization

    Speech Communication, Vol. 21, Núm. 3, pp. 141-153

  2. DFE-based algorithm for feature selection in speech recognition

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

  3. DISCRIMINATIVE FEATURE EXTRACTION FOR SPEECH RECOGNITION IN NOISE

    5th European Conference on Speech Communication and Technology, EUROSPEECH 1997

  4. STACC: AN AUTOMATIC SERVICE FOR INFORMATION ACCESS USING CONTINUOUS SPEECH RECOGNITION THROUGH TELEPHONE LINE

    5th European Conference on Speech Communication and Technology, EUROSPEECH 1997

1996

  1. An application of minimum classification error to feature space transformations for speech recognition

    Speech Communication, Vol. 20, Núm. 3-4, pp. 273-290