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  • 201.
    Zetterholm, Elisabeth
    et al.
    Department of Philosophy & Linguistics, Umeå University.
    Blomberg, Mats
    KTH, Superseded Departments, Speech, Music and Hearing.
    Elenius, Daniel
    KTH, Superseded Departments, Speech, Music and Hearing.
    A comparison between human perception and a speaker verification system score of a voice imitation2004In: Proc of Tenth Australian International Conference on Speech Science & Technology, 2004, p. 393-397Conference paper (Refereed)
    Abstract [en]

    A professional impersonator has been studied when training his voice tomimic two target speakers. A three-fold investigation has been conducted; acomputer-based speaker verification system was used, phonetic-acousticmeasurements were made and a perception test was conducted. Our ideabehind using this type of system is to measure how close to the target voice aprofessional impersonation might be able to reach and to relate this tophonetic-acoustic analyses of the mimic speech and human perception. Thesignificantly increased verification scores and the phonetic-acoustic analysesshow that the impersonator really changes his natural voice and speech in hisimitations. The results of the perception test show that there is no, or only asmall, correlation between the verification system and the listeners whenestimating the voice imitations and how close they are to one of the targetspeakers.

  • 202.
    Zhang, Xi
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Ottersten, Björn
    KTH, Superseded Departments, Speech, Music and Hearing.
    Power allocation and bit loading for spatial multiplexing in MIMO systems2003In: 2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS - SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO AND ELECTROACOUSTICS MULTIMEDIA SIGNAL PROCESSING, NEW YORK: IEEE , 2003, p. 53-56Conference paper (Refereed)
    Abstract [en]

    The power assignment problem is important for Multiple-Input-Multiple-Output (MIMO) systems to achieve high capacity. Although this problem is solved by well-known water filling algorithms, this does not provide an optimal solution if the system is constrained to a fixed raw bit error rate threshold and to discrete modulation orders. In this work an approximate approach, called QoS based WF, is proposed to solve the power assignment problem with such constrains. It is shown to outperform quantization of the conventional water filling solution and a well known bit loading algorithm (Chow's algorithm) used in the Digital Subscriber Lines (DSL).

  • 203. Öhlin, David
    et al.
    Carlson, Rolf
    KTH, Superseded Departments, Speech, Music and Hearing.
    Data-driven formant synthesis2004In: Proceedings FONETIK 2004: The XVIIth Swedish Phonetics Conference / [ed] Peter Branderud, Hartmut Traunmüller, Stockholm University, 2004, p. 160-163Conference paper (Other academic)
  • 204. Öhman, Tobias
    et al.
    Salvi, Giampiero
    KTH, Superseded Departments, Speech, Music and Hearing.
    Using HMMs and ANNs for mapping acoustic to visual speech1999In: TMH-QPSR, Vol. 40, no 1-2, p. 45-50Article in journal (Other academic)
    Abstract [en]

    In this paper we present two different methods for mapping auditory, telephonequality speech to visual parameter trajectories, specifying the movements of ananimated synthetic face. In the first method, Hidden Markov Models (HMMs)where used to obtain phoneme strings and time labels. These where thentransformed by rules into parameter trajectories for visual speech synthesis. In thesecond method, Artificial Neural Networks (ANNs) were trained to directly mapacoustic parameters to synthesis parameters. Speaker independent HMMs weretrained on a phonetically transcribed telephone speech database. Differentunderlying units of speech were modelled by the HMMs, such as monophones,diphones, triphones, and visemes. The ANNs were trained on male, female , andmixed speakers.The HMM method and the ANN method were evaluated through audio-visualintelligibility tests with ten hearing impaired persons, and compared to “ideal”articulations (where no recognition was involved), a natural face, and to theintelligibility of the audio alone. It was found that the HMM method performsconsiderably better than the audio alone condition (54% and 34% keywordscorrect, respectively), but not as well as the “ideal” articulating artificial face(64%). The intelligibility for the ANN method was 34% keywords correct.

2345 201 - 204 of 204
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