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Synthesis-based recognition of continuous speech

K K Paliwal, P V Rao

    The Journal of the Acoustical Society of America
    |April 1, 1982
    PubMed
    Summary
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    This study introduces an acoustic phonemic recognition system for continuous speech. Incorporating formant transition information significantly boosts speech recognition accuracy by utilizing both steady-state and transition segments.

    Area of Science:

    • Speech Recognition Technology
    • Acoustic Phonetics
    • Signal Processing

    Background:

    • Continuous speech recognition remains a challenge.
    • Utilizing formant transitions in speech signals can enhance recognition accuracy.
    • Existing systems often focus solely on steady-state speech segments.

    Purpose of the Study:

    • To develop and evaluate an acoustic phonemic recognition system for continuous speech.
    • To investigate the impact of incorporating formant transition information on recognition performance.
    • To improve the accuracy of continuous speech recognition systems.

    Main Methods:

    • A three-stage recognition process: segmentation, steady-state recognition, and synthesis-based recognition.
    • Utilizing both steady-state and transition segments of the speech signal.

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  • Employing a synthesis-based recognition approach to leverage formant transition data.

    • Main Results:

    • The system achieved 52.3% correct recognition using only steady-state segments.
    • Incorporating transition segments improved correct recognition to 62.0%.
    • Error rates included 5.4% missed segment error and 8.3% extra segment error.

    Conclusions:

    • The integration of formant transition information through a synthesis-based approach significantly enhances continuous speech recognition.
    • The proposed system demonstrates improved performance over methods relying solely on steady-state segments.
    • This approach offers a promising direction for advancing acoustic phonemic recognition.