Realizing Tibetan Lhasa speech concatenation synthesis system based on a large corpus

Zhenye Gan, Zhenwen Wang, Hongwu Yang
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Abstract

This paper presents a method to realize the Tibetan Lhasa speech concatenation synthesis based on a large corpus. A large corpus of Tibetan Lhasa dialect is established by analyzing the characteristics of Tibetan Lhasa dialect. A grapheme-to-phoneme conversion method is realized to convert Tibetan sentences to Speech Assessment Methods Phonetic Alphabet (SAMPA)-based Pinyin sequences. Firstly, Tibetan text is converted to Pinyin sequences based on SAMPA-T transformation method. Then the Tibetan acoustic finals and syllables are used as units to builds Classification and Regression Tree (CART) according to the spectral distance of each candidate units and the context dependent question sets. The CART algorithm is applied to choose the acoustic finals and syllables which are most conform to the context information. Finally, the Tibetan Lhasa speech is then synthesized by waveform concatenation synthesis method. Tests show that the MOS of Synthetic Tibetan Lhasa speech by using acoustic finals or syllables as units is 3.9 points and 4.1 points respectively. The quality of synthesized Tibetan Lhasa speech by using syllables as units is better than acoustic finals.
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基于大语料库的藏语拉萨语音拼接合成系统的实现
提出了一种基于大语料库的藏语拉萨语音拼接合成方法。通过对西藏拉萨方言特点的分析,建立了一个庞大的西藏拉萨方言语料库。实现了一种将藏文句子转换为基于语音评价方法音素(SAMPA)的拼音序列的字形音素转换方法。首先,利用SAMPA-T变换方法将藏文转换成拼音序列;然后以藏语声母和音节为单元,根据每个候选单元的谱距离和上下文相关问题集构建分类回归树(CART)。采用CART算法选择最符合上下文信息的韵母和音节。最后,采用波形串接合成的方法对西藏拉萨语音进行合成。测试结果表明,以声母和音节为单位的合成藏语拉萨语的最小分数分别为3.9分和4.1分。以音节为单位合成的拉萨语音质优于声母音质。
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