語聲出現率 的英文怎麼說

中文拼音 [yǔshēngchūxiànlǜ]
語聲出現率 英文
occurrence of speech sound
  • 語 : 語動詞[書面語] （告訴） tell; inform
  • 現 : Ⅰ名詞1 （現在; 此刻） present; now; current; existing 2 （現款） cash; ready money Ⅱ副詞（臨時; ...
  • 率 : 率名詞（比值） rate; ratio; proportion
  1. He has also shown how electronic technology can be harnessed to map out and account for phonological developments in china through the example of retroflex initials. mitsuaki endo follows the admirable tradition of toiling with patience and perseverence to provide a foundation that will facilitate research by others. he has compiled frequency data on initials, medials ( glides ), nucleus vowels, rhyme endings and tones in the chinese rhyme book

    遠藤光曉經過長期艱苦的努力，對《廣韻》中所出現的音位（聲母、介音、主要母音和聲調）進行了統計，並求出了各音位及各種語音類別的頻率，為今後從計算與計量的角度研究從中古到現代各方言的語音演變過程及原因提供了量化的依據。
  2. In this paper, the author provides frequency counts of the phonemes ( e. g. initials, medials, principal vowels, endings and tones ) and sound categories in the guangyun

    本文對《廣韻》中所出現的音位（即聲母、介音、主要母音、韻尾和聲調）進行統計，求出各音位及各種語音類別的頻率。
  3. The statistic of wavelet transform coefficient algorithm can solve the periodic noise, high - energy noise and some non - gauss noise simply and effectively ; bi - spectrum can acquire more information from the original signal than power - spectrum, detect more information except from range and restrain the gauss noise. short - time speech signal can be considered as stationary and with periodic non - gauss signal, so we can make use of bi - spectrum to obtain the speech character and separate the speech and noise and detect morse telegraph signal ; complex number spectrum variance algorithm is put forward based on the deeply observing speech data, it is a new algorithm, experiment show that it is simple, effective

    統計演算法在解決周期信號、高能噪聲和高斯信號方面有獨特之處，能簡單有效提取以上噪聲的特徵;雙譜能夠提供比功率譜更多的有用信息，有效地檢測信號幅度之外的其它信息，並能有效抑制高斯噪聲，短時語音信號一般認為是平穩且有一定的周期性的非高斯信號，因而可以利用雙譜來提取語音信號特性並實現信噪分離;復數譜方差演算法是在對語音信號進行深入觀察和分析的基礎上而提出來的一種全新的語音特徵提取方法，此方法簡單而有效的提取了語音、噪聲的特徵以及檢測莫爾斯信號，基於實驗表明，該演算法取得了很好的效果。
  4. The traditional detection algorithm, based on zero - crossing or energy, will not acquire ideal effect when the signal - to - noise is low or the signal is weaker. therefore, to resolve the real problem in the real environment that all kinds of random noise and speech signal exit together, some new algorithm must be put forward. account for the complexity of real noise, we integrate the wavelet transform and high - order statistics and advance a new algorithm ; the algorithm can effectively separate the speech signal and the non - gauss noise

    基於過零率和能量的傳統檢測演算法，在噪聲環境比較復雜的情況下效果很不穩定，尤其是信噪比較低或者語音信號較弱時，檢測效果很不理想，因此，在多種語言和噪聲隨機出現、噪聲和語音強弱不一的實際噪聲環境下，必須利用新的演算法提取有用信號和噪聲信號的有效特徵，才能解決實際的問題。
  5. The paper makes great efforts on the software optimization of evrc vocoder. based on the understanding of tms320c64xx cpu structure, we do deeply - optimization on the loop which appear usually in voice signal processing, and this improve the utility ratio of cpu and the parallelity degree of cpu function cell. at the same time, we utilize the bit - exact test to test the fixed - point evrc vocoder with the test vectors of tia / eia / is - 718, which improve the robustness of the vocoder

    本文圍繞定點evrc聲碼器的軟體優化，做了大量的工作，在充分理解tms320c64xxcpu結構的基礎上，針對語音信號處理中大量出現的循環運算進行了深度優化，大大提高了cpu的利用率以及cpu功能單元的并行程度，同時，我們還用tia / eia / is - 718的測試向量對定點evrc聲碼器進行了嚴格比特對準測試，提高了聲碼器的魯棒性。
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