基于乘法更新规则的语音参数非负时间分解

S. Hiroya
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引用次数: 8

摘要

我发明了一种基于乘法更新规则的线谱对和关节参数的非负时间分解方法。这些参数被分解成一组时间上重叠的单峰事件函数,限制在[0,1]范围内,以及相应的事件向量。当使用线谱对时,事件向量保持其有序属性。利用该方法,测得和重建的关节参数的均方根误差为0.21 mm,测得和重建的线谱对参数的谱距为2.0 dB。该方法的均方根误差和光谱距离均小于常规方法。该技术将在语音编码和语音修改的许多应用中发挥重要作用。
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Non-Negative Temporal Decomposition of Speech Parameters by Multiplicative Update Rules
I invented a non-negative temporal decomposition method for line spectral pairs and articulatory parameters based on the multiplicative update rules. These parameters are decomposed into a set of temporally overlapped unimodal event functions restricted to the range [0,1] and corresponding event vectors. When line spectral pairs are used, event vectors preserve their ordering property. With the proposed method, the RMS error of the measured and reconstructed articulatory parameters is 0.21 mm and the spectral distance of the measured and reconstructed line spectral pairs parameters is 2.0 dB. The RMS error and spectral distance in the proposed method are smaller than those in conventional methods. This technique will be useful for many applications of speech coding and speech modification.
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
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0.00%
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0
审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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