【摘要】：信息時(shí)代的企業(yè)變革崇尚以客戶為中心的服務(wù)理念�？蛻敉对V是整個(gè)客戶生命周期中客戶與企業(yè)的重要觸點(diǎn)。妥善的客戶投訴處理可以增加客戶的黏性、提升客戶對(duì)企業(yè)的忠誠度。在投訴處理過程中除了問題得到解決之外,對(duì)于客戶的情感體驗(yàn)也提出了更高的要求。目前的客戶投訴處理主要還是依托于電話語音平臺(tái),客戶投訴電話語音情感分析的研究對(duì)于改善投訴處理過程中的客戶體驗(yàn)具有非常重要的現(xiàn)實(shí)意義。電話的語音情感識(shí)別涉及語音處理、語義分析和模式識(shí)別等多種技術(shù)的綜合運(yùn)用,尤其在真實(shí)環(huán)境下,還必須考慮到電話背景噪聲的干擾以及連續(xù)對(duì)話中的情感動(dòng)態(tài)變化等復(fù)雜因素,現(xiàn)有的語音情感識(shí)別技術(shù)在實(shí)際應(yīng)用中還存在著較大的局限性。本文在作者親身工作經(jīng)歷和實(shí)踐的基礎(chǔ)上,重點(diǎn)研究了語音情感分析技術(shù)在客服呼叫中心領(lǐng)域的應(yīng)用。首先,從語音情感理論和PAC人格理論出發(fā),比較分析了不同語音情感分類方法的優(yōu)劣,介紹了PAC人格理論的概念和在不同服務(wù)行業(yè)中的應(yīng)用案例。然后以大量客戶投訴電話語音數(shù)據(jù)作為樣本進(jìn)行聽音分析,總結(jié)出客戶投訴電話中情感表達(dá)變化特征和影響情感變化的主要因素。在此基礎(chǔ)上,提出了語音情感分析技術(shù)的總體框架,并對(duì)其中語音情感信息預(yù)處理、特征參數(shù)提取、情感模式識(shí)別等關(guān)鍵技術(shù)做了詳細(xì)的研究,通過對(duì)比分析,最終選取了支持向量機(jī)(SVM)模式識(shí)別算法和Mel尺度倒譜參數(shù)(MFCC)來建立本文的識(shí)別模型。本文以真實(shí)電信投訴電話語音樣本庫為基礎(chǔ),采用LibSVM作為模式識(shí)別的算法類庫,基于Matlab環(huán)境構(gòu)建了投訴電話語音情感分析的試驗(yàn)平臺(tái)。對(duì)于投訴電話中平靜、不滿和憤怒三種典型客戶情感狀態(tài)以及客服人員和客戶的PAC對(duì)話模式進(jìn)行模式識(shí)別研究,取得了良好的識(shí)別效果,并且給出了動(dòng)態(tài)語音情感識(shí)別效果示意圖。最后還在實(shí)際應(yīng)用層面提出了基于客戶情感和PAC對(duì)話模式識(shí)別的客戶投訴處理流程。本文的研究成果為相關(guān)領(lǐng)域的研究工作提供了重要的參考與借鑒。
[Abstract]:Enterprise reform in the information age advocates the concept of customer-centered service. Customer complaint is an important contact point between customer and enterprise in the whole customer life cycle. Proper handling of customer complaints can increase customer viscosity and customer loyalty to the enterprise. In the process of handling complaints, in addition to the problem is resolved, the emotional experience of customers also put forward higher requirements. The current customer complaint processing mainly depends on the telephone voice platform. The research of customer complaint voice emotion analysis has very important practical significance to improve the customer experience in the process of complaint processing. The speech emotion recognition of telephone involves the comprehensive application of speech processing, semantic analysis and pattern recognition, especially in real environment. It is also necessary to take into account the complex factors such as the interference of telephone background noise and the dynamic change of emotion in continuous conversation. The existing speech emotion recognition technology still has some limitations in practical application. Based on the author's personal experience and practice, this paper focuses on the application of voice emotion analysis technology in the field of customer service call center. Firstly, based on speech emotion theory and PAC personality theory, this paper compares and analyzes the advantages and disadvantages of different speech emotion classification methods, and introduces the concept of PAC personality theory and its application in different service industries. Then a large number of customer complaints telephone voice data as a sample for listening analysis, summed up the customer complaints phone call emotional expression change characteristics and the main factors affecting emotional change. On this basis, the general framework of speech emotion analysis technology is put forward, and the key technologies, such as speech emotion information preprocessing, feature parameter extraction, emotion pattern recognition and so on, are studied in detail. Finally, support vector machine (SVM) (SVM) pattern recognition algorithm and Mel scale cepstrum parameter (MFCC) are selected to establish the recognition model in this paper. In this paper, based on the voice sample library of real telecom complaint telephone, LibSVM is used as the algorithm class library for pattern recognition. Based on the Matlab environment, the experimental platform for voice emotion analysis of complaint telephone is constructed. The pattern recognition for the three typical customer emotional states of calm, dissatisfaction and anger, and the PAC dialogue pattern between customer service personnel and customers, has been studied, and good results have been obtained. The effect of dynamic speech emotion recognition is illustrated. Finally, the process of customer complaint processing based on customer emotion and PAC dialogue pattern recognition is put forward in the practical application level. The research results of this paper provide an important reference for the research work in related fields.
【學(xué)位授予單位】：復(fù)旦大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN912.34

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本文編號(hào)：2392939