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    21.
    发明专利
    未知

    公开(公告)号：DE69727046T2

    公开(公告)日：2004-06-09

    申请号：DE69727046

    申请日：1997-10-15

    Applicant: MOTOROLA INC

    Inventor： CORRIGAN GERALD ,  KARAALI ORHAN ,  MASSEY NOEL

    IPC: G10L13/08

    Abstract: The present invention teaches a method (400), device and system (300) utilizing at least one of: mapping a sequence of phones to a sequence of articulatory features and utilizing prominence and boundary information, in addition to a predetermined set of rules for type, phonetic context, syntactic and prosodic context for phones to provide provide a system that generates segment durations efficiently with a small training set.

    Method,device and article of manufacture for neural-network based orthography-phonetics transformation
    28.
    发明专利
    Method,device and article of manufacture for neural-network based orthography-phonetics transformation 未知

    公开(公告)号：GB2326320B

    公开(公告)日：1999-08-11

    申请号：GB9812468

    申请日：1998-06-11

    Applicant: MOTOROLA INC

    Inventor： KARAALI ORHAN ,  MILLER COREY ANDREW

    IPC: G10L13/08 ,  G10L9/00

    Abstract: A method (2000), device (2200) and article of manufacture (2300) provide, in response to orthographic information, efficient generation of a phonetic representation. The method provides for, in response to orthographic information, efficient generation of a phonetic representation, using the steps of: inputting an orthography of a word and a predetermined set of input letter features; utilizing a neural network that has been trained using automatic letter phone alignment and predetermined letter features to provide a neural network hypothesis of a word pronunciation.

    A method and apparatus for converting text into audible signals using a neural network
    29.
    发明专利
    A method and apparatus for converting text into audible signals using a neural network 未知

    公开(公告)号：AU2104095A

    公开(公告)日：1995-11-29

    申请号：AU2104095

    申请日：1995-03-21

    Applicant: MOTOROLA INC

    Inventor： KARAALI ORHAN ,  CORRIGAN GERALD EDWARD ,  GERSON IRA ALAN

    IPC: G06F15/18 ,  G06N3/00 ,  G10L13/00 ,  G10L13/08

    Abstract: Text may be converted to audible signals, such as speech, by first training a neural network 106 using recorded audio messages 204. To begin the training, the recorded audio messages are converted into a series of audio frames 205 having a fixed duration 213. Then, each audio frame is assigned a phonetic representation 203 and a target acoustic representation 208, where the phonetic representation 203 is a binary word that represents the phone and articulation characteristics of the audio frame, while the target acoustic representation 208 is a vector of audio information such as pitch and energy. After training, the neural network 106 is used in conversion of text into speech. First, text that is to be convened is translated to a series of phonetic frames 401 of the same form as the phonetic representations 208 and having the fixed duration 213. Then the neural network produces acoustic representations in response to context descriptions 207 that include some of the phonetic frames 401. The acoustic representations are then converted into a speech wave form by a synthesizer 107.

    30.
    发明专利
    未知

    公开(公告)号：FI955608A

    公开(公告)日：1995-11-22

    申请号：FI955608

    申请日：1995-11-22

    Applicant: MOTOROLA INC

    Inventor： KARAALI ORHAN ,  CORRIGAN GERALD EDWARD ,  GERSON IRA ALAN

    IPC: G06F15/18 ,  G06N3/00 ,  G10L13/00 ,  G10L13/08 ,  G10L

    Abstract: Text may be converted to audible signals, such as speech, by first training a neural network 106 using recorded audio messages 204. To begin the training, the recorded audio messages are converted into a series of audio frames 205 having a fixed duration 213. Then, each audio frame is assigned a phonetic representation 203 and a target acoustic representation 208, where the phonetic representation 203 is a binary word that represents the phone and articulation characteristics of the audio frame, while the target acoustic representation 208 is a vector of audio information such as pitch and energy. After training, the neural network 106 is used in conversion of text into speech. First, text that is to be convened is translated to a series of phonetic frames 401 of the same form as the phonetic representations 208 and having the fixed duration 213. Then the neural network produces acoustic representations in response to context descriptions 207 that include some of the phonetic frames 401. The acoustic representations are then converted into a speech wave form by a synthesizer 107.

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