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Self-adaptive non-parallel training based voice conversion method

A voice conversion and adaptive technology, applied in speech analysis, speech recognition, instruments, etc., can solve the problems of difficulty in obtaining parallel corpus, inconvenient expansion of traditional voice conversion systems, etc., and achieve the effect of flexible and convenient system expansion.

Inactive Publication Date: 2014-10-29
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

[0006] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a new non-parallel corpus training voice conversion method to solve the following problems in the parallel corpus joint training voice conversion method: 1. In the traditional voice conversion system, parallel The conversion function is obtained through corpus training, but it is difficult to obtain parallel corpus; 2. The traditional speech conversion system needs joint training of feature vectors; 3. The expansion of the traditional speech conversion system is inconvenient

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[0019] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0020] figure 1 It is a flow chart of the voice conversion method of the optimized adaptive non-parallel training adopted by the present invention, as figure 1 As shown, the method includes the following steps:

[0021] Step 1, detecting an effective voice signal from the collected voice samples, and preprocessing the effective voice signal;

[0022] In an embodiment of the present invention, the preprocessing includes processing such as pre-emphasis, adding Hamming window, and framing.

[0023] Step 2, extracting speech feature parameters for the effective speech signal obtained after preprocessing;

[0024] The speech feature parameters may be pitch frequency, linear predictive cepstral coefficients (LPCC), Mel cepst...

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Abstract

The invention discloses a self-adaptive non-parallel training based voice conversion method. The method includes the steps: detecting effective voice signals from an acquired voice sample and preprocessing the effective voice signals; extracting voice characteristic parameters from the preprocessed effective voice signals; performing UBM (universal background model) training based on the voice characteristic parameters so as to obtain a UBM irrelevant to a speaker; obtaining an independent speaker voice model relevant to the speaker based on the UBM, and obtaining a conversion function of frequency spectrum parameters and base frequency parameters based on the independent speaker voice model; inputting the voice characteristic parameters of to-be-converted voice into the conversion function so as to obtain converted voice characteristic parameters of a target speaker; synthesizing the converted voice characteristic parameters of the target speaker so as to obtain target voice. The self-adaptive non-parallel training based voice conversion method not only has good conversion performance but also has good system expandability.

Description

technical field [0001] The invention relates to the fields of speech signal analysis, speech signal processing, speech conversion, speech synthesis and the like, in particular to a speech conversion method based on adaptive non-parallel training, which belongs to the speech conversion branch in the field of speech signal processing. Background technique [0002] Speech conversion refers to changing the speaker's personality characteristics under the premise of keeping the semantic content unchanged, so that the source speaker's voice sounds like the target speaker after the transformation. Speech conversion is an in-depth development of speech synthesis and recognition technology. As a new branch in the field of speech signal processing, speech conversion has high theoretical research value and application prospects. Learn from the knowledge in the fields of speech analysis and synthesis, speech recognition technology, speech codec technology, speech enhancement, speaker con...

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Application Information

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IPC IPC(8): G10L15/02G10L15/07G10L15/18
Inventor 王飞跃孔庆杰熊刚朱凤华朱春雷
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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