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Paavo Alku - One of the best experts on this subject based on the ideXlab platform.
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utilizing glottal source pulse library for generating improved Excitation Signal for hmm based speech synthesis
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
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ICASSP - Utilizing glottal source pulse library for generating improved Excitation Signal for HMM-based speech synthesis
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
Tuomo Raitio - One of the best experts on this subject based on the ideXlab platform.
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utilizing glottal source pulse library for generating improved Excitation Signal for hmm based speech synthesis
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
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ICASSP - Utilizing glottal source pulse library for generating improved Excitation Signal for HMM-based speech synthesis
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
Antti Suni - One of the best experts on this subject based on the ideXlab platform.
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utilizing glottal source pulse library for generating improved Excitation Signal for hmm based speech synthesis
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
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ICASSP - Utilizing glottal source pulse library for generating improved Excitation Signal for HMM-based speech synthesis
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
Hannu Pulakka - One of the best experts on this subject based on the ideXlab platform.
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utilizing glottal source pulse library for generating improved Excitation Signal for hmm based speech synthesis
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
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ICASSP - Utilizing glottal source pulse library for generating improved Excitation Signal for HMM-based speech synthesis
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
Martti Vainio - One of the best experts on this subject based on the ideXlab platform.
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utilizing glottal source pulse library for generating improved Excitation Signal for hmm based speech synthesis
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
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ICASSP - Utilizing glottal source pulse library for generating improved Excitation Signal for HMM-based speech synthesis
2011 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2011Co-Authors: Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Vainio, Paavo AlkuAbstract:This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is first decomposed into the glottal source Signal and the model of the vocal tract filter using glottal inverse filtering, and parametrized into Excitation and spectral features. Additionally, a library of glottal source pulses is extracted from the estimated voice source Signal. In the synthesis stage, the Excitation Signal is generated by selecting appropriate pulses from the library according to the target cost of the Excitation features and a concatenation cost between adjacent glottal source pulses. Finally, speech is synthesized by filtering the Excitation Signal by the vocal tract filter. Experiments show that the naturalness of the synthetic speech is better or equal, and speaker similarity is better, compared to a system using only single glottal source pulse.
