Data processing: speech signal processing – linguistics – language – Speech signal processing – Synthesis
Reexamination Certificate
2000-07-21
2004-08-17
Dorvil, Richemond (Department: 2654)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Synthesis
C704S268000, C704S269000
Reexamination Certificate
active
06778962
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to improvements in a speech synthesizing method, a speech synthesis apparatus and a computer-readable medium recording a speech synthesis program.
2. Description of the Related Art
The conventional method for outputting various spoken messages (language spoken by men) from a machine was a so-called speech synthesis method involving storing ahead speech data of a composition unit corresponding to various words making up a spoken message, and combining the speech data in accordance with a character string (text) input at will.
Generally, in such speech synthesis method, the phoneme information such as a phonetic symbol which corresponds to various words (character strings) used in our everyday life, and the prosodic information such as an accent, an intonation, and an amplitude are recorded in a dictionary. An input character string is analyzed. If a same character string is recorded in the dictionary, speech data of a composition unit are combined and output, based on its information. Or otherwise, the information is created from the input character string in accordance with predefined rules, and speech data of a composition unit are combined and output, based on that information.
However, in the conventional speech synthesis method as above described, for a character string not registered in the dictionary, the information corresponding to an actual spoken message, or particularly the prosodic information, can not be created. Consequently, there was a problem of producing an unnatural voice or different voice from an intended one.
SUMMARY OF THE INVENTION
It is an object of the present invention to provide a speech synthesis method which is able to synthesize a natural voice by absorbing a difference between a character string input at will and a character string recorded in a dictionary, a speech synthesis apparatus, and a computer-readable medium having a speech synthesis program recorded thereon.
To attain the above object, the present invention provides a speech synthesis method for creating voice message data corresponding to an input character string, using a word dictionary for storing a large number of character strings containing at least one character with its accent type, a prosody dictionary for storing typical prosodic model data among prosodic model data representing the prosodic information for the character strings stored in the word dictionary, and a waveform dictionary for storing voice waveform data of a composition unit with recorded voice, the method comprising determining the accent type of the input character string, selecting prosodic model data from the prosody dictionary based on the input character string and the accent type, transforming the prosodic information of the prosodic model data in accordance with the input character string when the character string of the selected prosodic model data is not coincident with the input character string, selecting the waveform data corresponding to each character of the input character string from the waveform dictionary, based on the prosodic model data, and connecting the selected waveform data.
According to the present invention, when an input character string is not registered in the dictionary, the prosodic model data approximating this character string can be utilized. Further, its prosodic information can be transformed in accordance with the input character string, and the waveform data can be selected, based on the transformed information data. Consequently, it is possible to synthesize a natural voice.
Herein, the selection of prosodic model data can be made by, using a prosody dictionary for storing the prosodic model data containing the character string, mora number, accent type and syllabic information, creating the syllabic information of an input character string, extracting the prosodic model data having the mora number and accent type coincident to that of the input character string from the prosody dictionary to have a prosodic model data candidate, creating the prosodic reconstructed information by comparing the syllabic information of each prosodic model data candidate and the syllabic information of the input character string, and selecting the optimal prosodic model data based on the character string of each prosodic model data candidate and the prosodic reconstructed information thereof.
In this case, if there is any of the prosodic model data candidates having all its phonemes coincident with the phonemes of the input character string, this prosodic model data candidate is made the optimal prosodic model data. If there is no candidate having all its phonemes coincident with the phonemes of the input character string, a candidate having a greatest number of phonemes coincident with the phonemes of the input character string among the prosodic model data candidates is made the optimal prosodic model data. If there are plural candidates having a greatest number of phonemes coincident with the phonemes of the input character string, a candidate having a greatest number of phonemes consecutively coincident with the phonemes of the input character string is made the optimal prosodic model data. Thereby, it is possible to select the prosodic model data containing the phoneme which is identical to and at the same position as the phoneme of the input character string, or a restored phoneme (hereinafter also referred to as a reconstructed phoneme), most coincidentally and consecutively, leading to synthesis of more natural voice.
The transformation of prosodic model data is effected such that when the character string of the selected prosodic model data is not coincident with the input character string, a syllable length after transformation is calculated from an average syllable length calculated beforehand for all the characters used for the voice synthesis and a syllable length in the prosodic model data for each character that is not coincident in the prosodic model data. Thereby, the prosodic information of the selected prosodic model data can be transformed in accordance with the input character string. It is possible to effect more natural voice synthesis.
Further, the selection of waveform data is made such that the waveform data of pertinent phoneme in the prosodic model data is selected from the waveform dictionary for a reconstructed phoneme among the phonemes constituting the input character string, and the waveform data of corresponding phoneme having a frequency closest to that of the prosodic model data is selected from the waveform dictionary for other phonemes. Thereby, the waveform data closest to the prosodic model data after transformation can be selected. It is possible to enable the synthesis of more natural voice.
To attain the above object, the present invention provides a speech synthesis apparatus for creating the voice message data corresponding to an input character string, comprising a word dictionary for storing a large number of character strings containing at least one character with its accent type, a prosody dictionary for storing typical prosodic model data among prosodic model data representing the prosodic information for the character strings stored in said word dictionary, and a waveform dictionary for storing voice waveform data of a composition unit with recorded voice, accent type determining means for determining the accent type of the input character string, prosodic model selecting means for selecting the prosodic model data from the prosody dictionary based on the input character string and the accent type, prosodic transforming means for transforming the prosodic information of the prosodic model data in accordance with the input character string when the character string of the selected prosodic model data is not coincident with the input character string, waveform selecting means for selecting the waveform data corresponding to each character of the input character string from the waveform dictionary, based on the prosodic model data, and waveform connecting means
Kasai Osamu
Mizoguchi Toshiyuki
Dorvil Richemond
Konami Corporation
Lerner Martin
Lowe Hauptman & Gilman & Berner LLP
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