F - formant 中文 - EN166

formant n.【語言】1.共振峰。2.構形成分。

format
Firstly , we study the construction of emotion - speech template database , and analyze the common features such as pitch , energy and formant . after choosing the useful features by using fuzzy entropy effectiveness analysis , we get better performance with the application of neural network . in addition , we propose some more efficient features such as speech rate , pitch slope , mel - frequency cepstral coefficients and its transient parameters , and design a processing model based on vector quantization for cepstral features to fusing different features 本文首先介紹了情感語音數據庫的建立情況,然后研究了基音頻率、振幅能量和共振峰等目前常用的情感特征在語音情感識別中的作用,并且通過一種基于模糊熵的特征有效性分析方法進行了有效特征的篩選,應用人工神經網絡建立了初步的語音情感識別模型,經過實驗發現特征篩選后系統的識別效果有著一定程度的提高。
In various speech character parameters , formant frequency , bandwidth and pitch frequency are chosen as voice character parameters . the reasons are as follows : hearing apperceive experiments indicates that formant frequency can stand for a majority of voice information , while average pitch frequency can explain 55 % ability of speaker verification 數據結果與多項式回歸和線性多變量回歸相比,支持向量回歸既提高了泛化性能又避免了頻譜不連續性,從而使轉換語音與目標語音的頻譜距離失真分別減少了33 . 29 %和35 . 24 % 。
This thesis tries to update the cmdsr system to achieve the characters below : real - time , better robust , higher recognition rate , non - special - man . considering the disadvantages of traditional improved spectrum subtraction speech enhancement , this thesis proposes the theory of fuzzy spectrum subtraction based on the fuzzy theory and improved spectrum subtraction speech enhancement ; as for the difficulties of detecting the endpoint of speech signal , the thesis gives the table of initial and the improved parameters , with which we can confirm the endpoints of mandarin digit speech ; the thesis puts forward two - level digit real - time speech recognition system , the first level is based on discrete hidden markov model which is linear predictive coding cepstrum ( lpcc ) and difference linear predictive coding cepstrum ( dlpcc ) , the second level is based on formant parameters ; as for the realization of hardware , the thesis depicts the realization of every part of cmdsr based on the tms320vc5402 in detail ; as for the development of software , the thesis gives the software design flow chart of cmdsr , simulates the basic theory with matlab language and gives the simulation results 針對傳統的“改進譜相減法語音增強”參數設定單一、環境適應能力差的缺點,提出了一種利用模糊理論和“改進的譜相減法”結合的“模糊譜相減法語音增強” ;針對語音信號端點檢測困難的特點,通過matlab仿真試驗,給出了能夠準確確定數碼語音端點的初始和改進參數表;提出了利用基于線性預測編碼倒譜參數和差分線性預測編碼倒譜參數相結合的離散隱含馬爾可夫模型進行第一級識別、利用共振峰參數進行第二級識別的兩級漢語數碼語音識別系統,在保證系統實時性的同時,實現連接漢語數碼語音識別系統識別率的提高;在硬件實現上,詳細闡述了基于tms320vc5402的連接漢語數碼語音識別系統各部分硬件設計;在軟件開發上,給出了連接漢語數碼語音識別的軟件設計各部分的流程圖,并對各部分進行了matlab仿真,并給出了仿真結果。
Moreover in speech enhancement , especially in reducing the pulse noise , morphological algorithm has its unique advantage . particularly morphological filter may maintain the preferable accurate of the speech signal in speech waveform , and which produces little impairment to the formant of speech . so the spectrum structure of the speech is retained well , and the quality of the speech will not be reduced 特別是，在時域波形分析中，形態學濾波增強較小波去噪更好地保持語音信號的細節；在頻域分析中，形態學濾波對語音信號的基音頻率、頻譜斜率、共振峰等語音特征的影響很小，因而能夠較好的保留語音信號的頻譜結構，使語音品質不致降低。
Carrying the information of content , it has the function of content verification . this article compares various method of formant parameters calculation , and completes the calculation of the 5 former formant frequencies and bands . as pitch frequency 在分別使用支持向量回歸和多項式回歸進行句子轉換的對比實驗中,支持向量回歸的頻譜更接近目標語音,但其執行速度慢,運算時間較長。
The results of simulation indicated speech signal processed by the optimum algorithm presents obvious periodicity in time domain , and effect of the formant is removed or restrained effectively in frequency domain 處理后的語音信號在時域上表現出明顯的周期性特征，同時在頻域上也觀察到聲道的共振峰結構影響得到消除或有效的抑制。
Formant : it uses the estimation of the overall shape of the spectrum ' s amplitude envelope 共振峰:使用了對頻譜的振幅包絡線的大體形狀所作的估計。
A novel speaker normalization method based on formant recovery and mellin transform 基于子波變換的自適應濾波語音增強方法
Automatic formant analysis 自動共振峰分析
Formant frequency of vowel 元音的共振峰頻率