Extraction of speaker-specific features from spoken code sentences
In the speaker-verification task speakers are assumed to be cooperative and are therefore willing to pronounce a pre-arranged code sentence. This paper deals with the extraction of speaker-specific features from a time-normalized parametric description of the code sentence. A new mml (minimum-maximu...
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Published in | ICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing Vol. 3; pp. 279 - 282 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
1978
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Abstract | In the speaker-verification task speakers are assumed to be cooperative and are therefore willing to pronounce a pre-arranged code sentence. This paper deals with the extraction of speaker-specific features from a time-normalized parametric description of the code sentence. A new mml (minimum-maximum-locating) method for time-normalization is presented together with an overview of techniques used for feature-extraction. Results of recognition experiments are discussed, which have been obtained with the AUROS system (Automatic Recognition of Speakers by Computers). |
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AbstractList | In the speaker-verification task speakers are assumed to be cooperative and are therefore willing to pronounce a pre-arranged code sentence. This paper deals with the extraction of speaker-specific features from a time-normalized parametric description of the code sentence. A new mml (minimum-maximum-locating) method for time-normalization is presented together with an overview of techniques used for feature-extraction. Results of recognition experiments are discussed, which have been obtained with the AUROS system (Automatic Recognition of Speakers by Computers). |
Author | Talmi, M. Jesorsky, P. Hofker, U. |
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PublicationTitle | ICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing |
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Snippet | In the speaker-verification task speakers are assumed to be cooperative and are therefore willing to pronounce a pre-arranged code sentence. This paper deals... |
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StartPage | 279 |
SubjectTerms | Bandwidth Computer science Feature extraction Hardware Pattern recognition Production systems Speech analysis Speech coding Speech processing Stress |
Title | Extraction of speaker-specific features from spoken code sentences |
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