本文選題：語音識別 + 構(gòu)音障礙評估��； 參考：《華東師范大學(xué)》2014年博士論文

【摘要】：我國言語構(gòu)音、語音障礙患者數(shù)量較多,而相關(guān)的障礙評估方法主要以主觀聽覺感知為主,缺乏一定的客觀性和穩(wěn)定性。近年來,語音識別技術(shù)在多個領(lǐng)域得到了廣泛的應(yīng)用,在言語語言教育方面的應(yīng)用研究也取得了一定成果。但是在言語障礙評估與康復(fù)研究領(lǐng)域,基于語音識別的相關(guān)研究成果并不多見,而且未能引起足夠的重視。本研究根據(jù)國內(nèi)外言語構(gòu)音、語音障礙的評估方法研究現(xiàn)狀和發(fā)展趨勢,綜合語音識別技術(shù)在言語語言教育中應(yīng)用的研究成果,進行了言語構(gòu)音障礙、語音障礙自動評估的探索性研究。 本研究首先提出基于語音識別進行構(gòu)音障礙自動評估的基本思想,即能夠通過計算機等設(shè)備對患者的構(gòu)音功能從內(nèi)容、聲調(diào)以及障礙類型三方面進行自動評價。為驗證基于語音識別的構(gòu)音障礙自動評估方法的可行性,本研究基于微軟公司發(fā)布的自帶識別引擎的Speech SDK開發(fā)了構(gòu)音障礙自動評估可行性分析系統(tǒng)。通過比較使用該系統(tǒng)和主觀聽覺感知方法對3-6歲健聽兒童的構(gòu)音能力評估的結(jié)果,得到構(gòu)音障礙自動評估可行性分析系統(tǒng)對全部被試的平均識別準確率達到83.5%,初步說明基于語音識別的構(gòu)音障礙評估方法是可行的,但仍無法滿足言語障礙評估與康復(fù)的臨床實際需求。 本研究也因此提出了基于改進技術(shù)方案的構(gòu)音障礙自動評估方法。采用自行構(gòu)建的識別引擎和微軟內(nèi)置的識別引擎構(gòu)建“雙識別引擎”的構(gòu)音障礙自動評估系統(tǒng)。首先,本研究采用基于隱馬爾科夫模型的語音識別算法,從整體平均的角度來實現(xiàn)最優(yōu)的識別過程,在統(tǒng)計框架中尋找能夠使模型參數(shù)最大化的詞條作為識別結(jié)果。提取62名3-6歲健聽兒童按照指定詞表所發(fā)語音的39維參數(shù)制作標準聲學(xué)模型。根據(jù)前人對聽障兒童構(gòu)音障礙評估的研究成果,得到普通話聲母和韻母的常見構(gòu)音障礙具體情況,將構(gòu)音障礙產(chǎn)生的詞條匯總成表。基于微軟Speech SDK實現(xiàn)構(gòu)音障礙類型的檢測模塊。最后,基于SMDSF算法提取語料的4維基頻特征,制作用于實現(xiàn)聲調(diào)識別的標準聲調(diào)識別模型。效果驗證包括兩方面,一方面使用與構(gòu)音障礙自動評估可行性分析實驗相同的健聽兒童語料來驗證系統(tǒng)的識別性能,識別準確率達到98%以上；另一方面采用主觀聽覺感知評估與語音識別評估對比的方式,對3-5歲的聽障兒童的構(gòu)音能力進行評估。結(jié)果證明兩種方法得到的結(jié)果沒有顯著性差異,四項構(gòu)音清晰度指標的值基本一致,能夠基本實現(xiàn)構(gòu)音障礙的自動評估。 在構(gòu)音障礙自動評估系統(tǒng)構(gòu)建的基礎(chǔ)上,本研究通過改進識別算法提出了語音障礙自動評估系統(tǒng)。在自行構(gòu)建的標準聲學(xué)模型基礎(chǔ)上,分別提出了《語音重復(fù)能力測驗詞表》和《語音切換能力測驗詞表》以及基于這些詞表的語音障礙自動評估方法。然后,同樣基于微軟Speech SDK提供的具備優(yōu)先識別指定詞條功能的API函數(shù),實現(xiàn)語音重復(fù)和語音切換的障礙檢測。最后,以聽障兒童為對象,采用主觀聽覺感知評估與構(gòu)音識別評估對比的方式,對語音障礙自動評估系統(tǒng)進行效果驗證。結(jié)果證明。語音障礙自動評估系統(tǒng)的評估結(jié)果與主觀評估結(jié)果沒有顯著性差異,兩種方法得到的評估指標結(jié)果基本一致,能夠基本實現(xiàn)語音重復(fù)能力和語音切換能力的自動評估功能。
[Abstract]:In our country, the number of speech sounds and speech disorders is large, and the related obstacle assessment methods are mainly subjective auditory perception and lack of objectivity and stability. In recent years, speech recognition technology has been widely used in many fields, and some achievements have been achieved in the application and research of speech language education. In the field of language barrier assessment and rehabilitation research, the related research results based on speech recognition are not very common, and they have not been paid enough attention. This study is based on the research status and development trend of the evaluation methods of speech disorders at home and abroad, and the research results of the application of speech recognition technology to speech language education. An exploratory study of automatic assessment of dysarthria and speech disorders.
In this study, the basic idea of automatic evaluation of dysarthria based on speech recognition is first proposed, that is, it can be automatically evaluated from three aspects of content, tone and obstacle type by computer and other devices. This study is based on the feasibility of the automatic evaluation method based on speech recognition. This study is based on Microsoft. The Speech SDK issued by the company has developed an automatic evaluation feasibility analysis system for dysarthria. By comparing the results of the system and the subjective auditory perception method for the assessment of the sound building ability of 3-6 year old healthy children, the average recognition accuracy of the system is obtained for all the subjects. Up to 83.5%, it shows that the speech recognition based articulation disorder assessment method is feasible, but it still can not meet the clinical needs of speech impairment assessment and rehabilitation.
In this study, an automatic evaluation method based on improved technical scheme is proposed. The self constructed recognition engine and the built-in recognition engine of Microsoft are used to construct a "double recognition engine" automatic evaluation system. Firstly, the speech recognition algorithm based on the hidden Markov model is used in this study, from the overall average. In order to achieve the best recognition process, we find a word which can maximize the parameters of the model in the statistical framework. 62 children of 3-6 years old are extracted according to the 39 dimension parameters of the speech on the specified word list. According to the previous research results of the impairment assessment of the sound barrier of the hearing impaired children, the Chinese consonant is obtained. And the specific situation of the common sound barrier of vowel, the words which are generated by the dysarthria are summarized into tables. Based on the Microsoft Speech SDK, the detection module of the dysarthria type is realized. Finally, based on the SMDSF algorithm, the 4 dimension fundamental frequency characteristics of the corpus are extracted, and the standard tone recognition model for tone recognition is made. The effect verification includes two aspects, on the one hand We use the same sound hearing children's corpus to verify the recognition performance of the system, and the recognition accuracy is above 98%. On the other hand, we use the way of subjective auditory perception assessment and speech recognition evaluation to evaluate the sound building ability of the 3-5 year old hearing impaired children. The results prove that two kinds of methods are used. There is no significant difference in the results obtained by the method. The four articulation indices are basically the same, which can basically achieve the automatic assessment of articulation disorders.
On the basis of the construction of the automatic evaluation system for dysarthria, an automatic speech obstacle evaluation system is proposed by improving the recognition algorithm. On the basis of the standard acoustic model constructed by ourselves, the speech repeating ability test word list > speech switching ability test word list > and the speech barrier based on these words are proposed respectively. And then, based on the API function provided by Microsoft Speech SDK, which has the priority to identify the function of the specified word, it realizes the obstacle detection of speech repetition and speech switching. Finally, the hearing impaired children are used to compare the subjective auditory perception assessment and the construction of the speech recognition evaluation, and the effect of the speech obstacle automatic evaluation system is achieved. The results show that there is no significant difference between the evaluation results of the speech obstacle automatic evaluation system and the subjective evaluation results. The results of the two methods are basically the same, and can basically realize the automatic evaluation function of the speech repetition ability and the voice switching ability.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN912.3

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