利用小波听觉分频处理与讯号子空间分解於车内噪音消除.doc

利用小波聽覺分頻處理與訊號子空間分解於車內噪音消除王駿發、楊宗憲、張凱行摘要在傳統的訊號子空間語音強化方法(Signal Subspace Speech Enhancement Method)中，其主要是利用噪音能量是均勻分佈於訊號所在的向量空間而語音訊號能量則是分佈於某一子空間的特性，藉由特徵分解(Eigen-Decomposition)來分析出語音訊號及背景噪音，來進行噪音消除。而在車內噪音環境中，噪音能量的分佈在低頻帶為最多延伸到高頻則逐漸較少，單一的訊號子空間的語音強化方法已不能更有效的消除位在低頻帶的背景噪音。本論文提出一個基於人耳聽覺特性的分頻處理，並結合訊號子空間強化方法來克服此一問題。實驗的驗證，則是採用TAICAR車內語音資料庫來進行，實驗結果說明本文所提出的方法比起傳統訊號子空間強化法，更適用於車內噪音的消除，低頻噪音的消除也更明顯。聚集事後機率線性迴歸調適演算法應用於語音辨識Aggregate a Posteriori Linear Regression for Speech Recognition黃志賢、王奕凱、簡仁宗摘要在本論文中，我們提出一套由聚集事後機率(aggregate a posteriori)為基礎之鑑別式線性回歸(linear regression) 轉換矩陣參數調適演算法。在近幾年，由於鑑別式訓練的效果優越，於是出現使用鑑別式訓練法則進行轉換矩陣調適，稱為最小分類錯誤率線性迴歸(minimum classification error linear regression, MCELR)調適演算法。我們認為使用最小分類錯誤率準則進行線性迴歸調適時，若能再進一步考慮線性迴歸矩陣之事前機率分佈，則可以結合貝氏法則之強健性與最小分類錯誤率之鑑別性，以估測出更佳之轉換矩陣用於語者調適上。透過聚集事後機率與鑑別式訓練間之關連及適當之條件簡化，則可得到參數更新之封閉解(close form)型式以加速鑑別式訓練的參數估測。在實驗中，我們使用TCC300 語料進行語音模型參數之訓練與迴歸矩陣之事前機率分佈之參數估測，而在調適及測試時，則使用公共電視台所錄製之電視新聞語料，進行轉換矩陣估測強健性之評估與其他轉換矩陣參數調適效能之比較，在不同調適語料之實驗結果發現我們提出之聚集事後機率線性回歸可以有效達到鑑別式語者調適的效果。非監督式學習於中文電視新聞自動轉寫之初步應用郭人瑋、蔡文鴻、陳柏琳摘要.本論文探討非監督式學習於中文電視新聞自動轉寫之初步應用。在聲學模型訓練上，我們提出以發音確認(Utterance Verification)技術來克服訓練語料沒有正確人工轉寫的問題，所謂的發音確認是使用候選詞信心度評估(Candidate Word Confidence Measure)來對某語句及其轉寫進行篩選的動作，用以決定此語句及轉寫是否有足夠的可靠度，進而成為訓練語料。我們先使用大詞彙連續語音辨識器對龐大且無人工轉寫的語料進行自動轉寫，再使用發音確認(Utterance Verification)針對辨識後的語料進行篩選，從中擷取較正確可靠的語料片段，以供聲學模型訓練使用，此舉不僅可大大節省人力成本，在效果上，經訓練過的聲學模型也和單純以人工轉寫結果所訓練出來的模型相距不遠；同時，較正確可靠的文字語料片段，則用於語言模型調適，以增進辨識效能。同樣地，候選詞信心度評估也被應用到非監督式聲學模型調適上，我們初步將它與最大相似度線性迴歸(Maximum Likelihood Linear Regression)聲學模型調適技術作結合，以語音辨識所產生之詞圖(Word Graph)作為調適標的。我們以公共電視台的新聞語料為研究題材，結果顯示非監督式聲學模型訓練與調適的結合的確可有效降低字錯誤率(Character Error Rate)，驗證了此作法之可行性。A Noise Estimator with Rapid Adaptation in Variable-Level Noisy EnvironmentsBing-Fei Wu, Kun-Ching Wang, Lung-Yi KuoAbstractIn this paper, a noise estimator with rapid adaptation in a variable-level noisy environment is presented. To make noise estimation adapt quickly to highly non-stationary noise environments, a robust voice activity detector (VAD) is utilized in this paper and it depends on the variation of the spectral energy not on the amount of that. The noise power spectrum in subbands are estimated by averaging past spectral power values using a time and frequency dependent smoothing parameter, which is chosen as a sigmoid function changing with speech-present probability in subbands. The speech-present probability is determined by computing the ratio of the noisy speech power spectrum to its local minimum. Noise measurement, speech enhancement, spectral analysis, signal process.A Three-Phase System for Chinese Named Entity RecognitionConrad Chen, Hsi-Jian LeeAbstractThe handling of out-of-vocabulary (OOV) words is one of the key points to a high performance lexical analysis in natural language processing. Among all OOV words, named entities (NE) are the most productive ones. They generally constitute the most meaningful parts of sentences (persons, affairs, time, places, and objects). In this paper, we propose a three-phase “generation, filtering, and recovery” system to address the NER problem. A set of stochastic models is first used to generate all possible NE candidates. Then we treat candidate filtering as an ambiguity resolution problem. To resolve ambiguities, we adopt a maximal-matching-rule-driven lexical analyzer. Last, a pattern matching method is applied to detect and recover abnormalities in the results of the previous two phases.Pure lexical information is exploited in our system. We get a high recall of 96% with personal names (PER), satisfiable recall of 88%, 89%, and 80% with transliteration names (TRA), location names (LOC), and organization names (ORG), respectively. The overall precision and excluding rate is over 90% and 99%.主題導向之非結構化文本資訊擷取技術劉吉軒、翁嘉緯Abstract資訊擷取(information extraction)是從自然語言文本中辨出特定主題或事件的描述，進而萃取出相關主題或事件元素的對應資訊，如人、事、時、地、物等。因此，資訊擷取技術能依照需要的主題與事件，自動的解讀自然語言文件，將文件中的原始文字資轉換成結構化的核心資訊。在本論文，我們提出以型態辨識的方法來處理主題導向的非結構化文本資訊擷取的問題。我們以總政府人事任免公報為測試對象，其精確率為98%、回收率為97%，充分印證了本資訊擷取方法處裡主題導向之資訊擷取問題的可行性。Finding Relevant Concepts for Unknown Terms Using a Web-based ApproachChen-Ming Hung and Lee-Feng ChienAbstractPrevious research on automatic thesaurus construction most focused on extracting relevant terms for each term of concern from a small-scale and domain-specific corpus. This study emphasizes on utilizing the Web as the rich and dynamic corpus source for term association estimation. In addition to extracting relevant terms, we are interested in finding concept-level information for each term of concern. For a single term, our idea is that to send it into Web search engines to retrieve its relevant documents and we propose a Greedy-EM-based document clustering algorithm to cluster them and determine an appropriate number of relevant concepts for the term. Then the keywords with the highest weighted log likelihood ratio in each cluster are treated as the label(s) of the associated concept cluster for the term of concern. With some initial experiments, the proposed approach has been shown its potential in finding relevant concepts for unknown terms.以自組織映射圖進行計算語言學領域術語視覺化之研究Visualizing the Terms of Computational Linguistics林頌堅Sung-Chien Lin摘要本論文的研究利用自組織映射圖(SOM)技術將計算語言學相關術語對應到二維圖形， 使得術語之間關係可以在中加以呈現，提供使用者做為資訊檢索以及了解重要研究主題輔助工具。本論文中，我們所探討的問題有(1)發展SOM技用術語資訊視覺化的方法，(2)評估SOM技術應用到術語資訊視覺化的成效，(3)利研究結果分析計算語言學中重要的研究主題與主題之間的關係。在SOM技術應中，首先從論文料中抽取重要術語，接著以術語共現做為基礎，建立每一個術語的特徵向量。再以術語特徵向量做為輸入資料，進行SOM訓練以及將語映射到圖形上。對於這項技術在應用上的成效評估，由於映射節點的距離關係在視覺上要需符合間相關性因此，我們建議以特徵向量的距離與位置的距離之間的相關係數做為成效評估的標準。最後， 對於計算語言學領域術語所進行實驗中可以發現大多相關的術語都可以映射到相鄰近的節點上，而術語所映射節點也大致表主題之間係。這個結果表示SOM技術適合應用於資訊視覺化。Applying Meaningful Word-Pair Identifier to the Chinese Syllable-to-Word Conversion ProblemJia-Lin Tsai, Tien-Jien Chiang and Wen-Lian HsuAbstractSyllable-to-word (STW) conversion is a frequently used Chinese input method that is fundamental to syllable/speech understanding. The two major problems with STW conversion are the segmentation of syllable input and the ambiguities caused by homonyms. This paper describes a meaningful word-pair (MWP) identifier that can be used to resolve homonym/segmentation ambiguities and perform STW conversion effectively for Chinese language texts. It is designed as a support system with Chinese input systems. In this paper, five types of meaningful word-pairs are investigated, namely: noun-verb (NV), noun-noun (NN), verb-verb (VV), adjective-noun (AN) and adverb-verb (DV). The pre-collected datasets of meaningful word-pairs are based on our previous work auto-generation of NVEF knowledge in Chinese (AUTO-NVEF) 30, 32, where NVEF stands for noun-verb event frame.The main purpose of this study is to illustrate that a hybrid approach of combining statistical language modeling (SLM) with contextual information, such as meaningful word-pairs, is effective for improving syllable-to-word systems and is important for syllable/speech understanding. Our experiments show the following: (1) the MWP identifier achieves tonal (syllables with four tones) and toneless (syllables without four tones) STW accuracies of 98.69% and 90.7%, respectively, among the identified word-pairs for the test syllables; (2) by STW error analysis, we find that the major critical problem of tonal STW systems is the failure of homonym disambiguation (52%), while that of toneless STW systems is inadequate syllable segmentation (48%); (3) by applying the MWP identifier, together with the Microsoft input method editor (MSIME 2003) and an optimized bigram model (BiGram), the tonal and toneless STW improvements of the two STW systems are 25.25%/21.82% and 12.87%/15.62%, respectively.Keywords: syllable-to-word, contextual information, top-down identifier, n-gram model.語料庫統計值與全球資訊網統計值之比較：以中文斷詞應用為例林筱晴、陳信希摘要近年來全球資訊網(World Wide Web，簡稱Web)快速成長，不同來源、不同領域、不同媒體的資訊透過網路傳遞到使用者手上。Web 除了扮演資訊傳播的角色外，也可以被視為是一個超大的資料集，提供語料庫為基礎統計導向方法(Corpus-Based Statistics-Oriented Approach)所需要的統計值。本文以中文斷詞應用為例，由傳統語料庫和全球資訊網中，取得運用word-based n-gram model 解斷詞歧義時所需要的統計值，藉以比較傳統語料庫和全球資訊網的差異。在第一組實驗，我們假設完全沒有未知詞，運用傳統語料庫的統計值最佳，其次依序為Google 為基礎,AltaVista 為基礎、和 Openfind 為基礎。在第二組實驗，我們針對指定實體辨識，地名和組織名這兩類有不錯的效能。在第三組實驗，我們整合斷詞系統與指定實體辨識模組，全球資訊網統計值比傳統語料庫的統計值好。在最後一組實驗，我們將傳統語料庫和全球資訊網混合在一起，以全球資訊網統計值解決未知詞問題，再以語料庫統計值解斷詞歧義性，實驗顯示具有最佳的斷詞效能。Pronominal and Sortal Anaphora Resolution for Biomedical LiteratureYu-Hsiang Lin and Tyne LiangAbstract.Anaphora resolution is one of essential tasks in message understanding. In this paper resolution for pronominal and sortal anaphora, which are common in biomedical texts, is addressed. The resolution was achieved by employing UMLS ontology and SA/AO (subject-action/action-object) patterns mined from biomedical corpus. On the other hand, sortal anaphora for unknown words was tackled by using the headword collected from UMLS and the patterns mined from PubMed. The final set of antecedents finding was decided with a salience grading mechanism, which was tuned by a genetic algorithm at its best-input feature selection. Compared to previous approach on the same MEDLINE abstracts, the presented resolution was promising for its 92% F-Score in pronominal anaphora and 78% F-Score in sortal anaphora.用自然語言處技術自動產生英文克詞試題之研究王俊弘、昭、高照明摘要電腦輔助產生試題系統的研究熱潮正方興未艾，其研究目的在於節人以建置大規模的題庫，並進一步支援網學習、成效評估與適性化測驗。受惠於自網際網上充裕的文字資源，吾人可以用既有的語產生涵蓋各種同主題的克詞試題，以增加題庫的多樣性。另一方面，由於電腦輔助產生試題系統減少人為的干預，也得以保持試題隱密性。我們提出一個詞義辨析的演算法，用詞典與selectional preference 所提供的資訊，分析試題的答案的詞義，並以collocation 為基礎的方法篩選誘答選項。實驗結果顯示我們的系統可在每產生1.6 道試題中，得到1 道可用的試題。Key Words:試題編寫工具與方法、自動化產生試題、電腦輔助語言學習、詞義辨析、自然語言處、collocations、selectional preferencesAn Infrastructure for Creating Web Automation ApplicationsWen Heng Yen, Hao-Ren Ke, and Wei-Pang YangAbstractWith the growth of the World Wide Web (WWW), many people nowadays spend a lot of time performing various tasks with browsers, most of these tasks repetitive and tedious. Many applications are created to reorganize and simplify the usage of Web resources, which are called Web automation applications. This paper proposes an infrastructure to create Web automation applications, the WIS (Web Integration Solution) system. WIS integrates a diversity of tools and technologies to provide a software environment for developing Web automation services. Developers can use this tool to create various Web automation applications. We show the versatility of WIS by implementing three exemplary services. The first is a metasearcher system that provides a single search interface for several indexing and abstract databases. The second is a cataloguing tool to simplify the task of retrieving bibliographic data from the Web; this tool is also integrated with a book-recommendation system for libraries. The third is a Web site checking system that periodically checks if some critical Web sites are working correctly, no matter how complex the check procedure is.Keywords: User Surrogates; Web Agent; Web Automation現代漢語複合動詞之詞首詞尾研究邱智銘，駱季青，陳克健摘要一般探討現代漢語複合動詞(compound verbs)，不外乎提到動補結構(verb-result)、動賓結構(verb-object)、並列結構(verb-verb)以及偏正結構(adverb-verb)四種類型，但卻鮮少提及複合成分(modifier-modifee)與其複合後所形成的動詞語意及與句法之互動。本文主要是探討複合動詞(以詞庫小組1993標記後的複合動詞)的組成，此可分為兩類來分析Fab,2001：一類為區分前後述詞的關連性及本身屬性predicator-predicator relation)，區分複合動詞的核心述詞(Head)以及輔助述詞(verbal satellite)；另一類為區分述詞及論元的關連性及本身屬性(predicator-argument relation)。藉由中央研究院現代漢語平衡語料庫(Sinica Corpus)找出衍生性強的詞首(morpheme-initial)及詞尾(morpheme-final)，在這兩類中的所扮演的語意角色(semantic role)及複合後的語法功能。語法規律的抽取及普遍化與精確化的研究Grammar Extraction, Generalization and Specialization謝佑明、楊敦淇、陳克健摘要相較於傳統PCFG的CNF處理，在本篇論文中，我們提出二元化句法規則產生模式。並且深入探討其語法普遍化與精確化方法對中文剖析器的影響。實驗設計從中研院中文句結構樹中依不同的語法抽取原則，抽取出不同的語法規律集合，來剖析三份測試語料並評估結果。觀察結果試著去尋找出有效的語法普遍化及精確化方法，得到覆蓋率高且精確的句法規則，以加強中文剖析器的剖析效能。剖析精確率的實驗結果，從基本普遍化語法的81.45%增加到精確化語法的86.14%。關鍵詞：覆蓋率、語法歧義、句法剖析、語法抽取A Resolution for Polysemy: the case of Mandarin verb ZOU (走)Yaling Hsu, Meichun LiuAbstractIn this paper, we propose a procedural schema as a model of cognitive processing of word senses, which can be viewed as a derivational resolution of polysemy. Previous researches, such as Frame -Based Lexicon by Fillmore 4 and Lexical Semantics by Cruse 2, are all concerned with word senses, but what is still missing is a holistic resolution of polysemy. Therefore, in this paper, we focus on the cognitive process from word form to word senses, based on corpus-based procedural resolution. In this way, we hope to provide an overall discussion and a computerizable way of solving multiplicity of semantic usages of a single word form. A case study of the Mandarin verb ZOU (走) is presented and used as an illustration.Too Good to Be True: A Case Study of “Zui Hao Shi”Hsiang-nan (Gustav) ChouAbstractThis paper aims to investigate the polysemy and multifunctionality of the expression “最好是”. It has been observed in recent years that “最好是” has two different meanings and semantic-pragmatic functions. The first function is to express speakers suggestion or expectation to the hearers to reach the optimal outcome. It is noted as the deontic optative meaning by Bybee (Bybee et al. 1994). As this meaning expresses expectation to the events in a hypothetical world, the deontic “最好是” also functions as a conditional marker (Traugott 1983). The other meaning of 最好是 is the epistemic meaning. The epistemic meaning of 最好是 performs the indirect speech act to show the speakers denial or disbelief brought forth by the interlocutor. The paper is to argue that the epistemic meaning of “最好是” derives from the deontic meaning. This semantic change is motivated by subjectification of the semantic implication of deontic meaning, which consists of implicature of “not yet done” and “too good to be true”. The data for this paper consists of three main sources: on-line corpus (Academia Sinica Balanced Corpus), Internet (google and yahoo), and conversation data. The three databases consists of different types of discourse (written and spoken) and different levels of formality. The observation from the data shows that the process of semantic change of 最好是 follows the path of semantic change proposed by Traugott and Dasher (2002). The epistemic meaning of 最好是 derives from the deontic meaning as the result of subjectification of the semantic implications (Traugott 1999). The distribution of data also points out that the epistemic “最好是” is informal and requires an interactional context while the deontic “最好是” appear much more frequently in formal context and written discourse. At last, according to the data, it is proposed that the epistemic “最好是” should be established as an epistemic formula. This formulaic form of “最好是” functions as verbal irony. It serves as an option for politeness strategy (Brown and Levinson 1987) to soften and counter direct criticism, complaints, and disbelief.FUNCTIONAL DISTINCTION BETWEEN ZAI (在) AND ZHENGZAI (正在) IN MANDARINLin, Tsi-chun Liu, Mei-chunAbstractBoth zai and zhengzai are progressive markers in Mandarin Chinese, and by the principle of economy, there should be some differences in these two progressive markers. With the Sinica Corpus on-line tools, a significant difference is found in the collocation of adverbial adjuncts with the use of zai and zhengzai. This paper discusses three types of adverbials to distinguish these two markers: modality adverbs, time adverbs, and manner adverbs. Zhengzai cannot co-occur with +iterative adverbs and adverbs without a specific time reference. It mainly indicates the progression of an on-going event at a given specific time point. On the other hand, zai not only indicates the on-going process but can also signal the progression of repeated event as habitual- progressive.中文手機新聞簡訊自動摘要曾元顯摘要台灣地區手機的普及率已居全球之冠，國內外產業界陸續開始提供手機新聞簡訊的服務。由於手機螢幕不大，手機上新聞簡訊的自動摘要要求，與一般文獻探討的不同。為保障訂閱者的權利，其摘要長度必須盡可能接近但不超過指定的字數，如69 字或45 字。此指定字數比一般標題長但比長句子還短，而且必須把新聞的重點盡可能完整的呈現出來。由於此摘要是提供給人閱讀，所以還要考慮其可讀性與連貫性等因素。本文提出一套適用於中文手機環境的新聞簡訊自動摘要方法，以降低新聞簡訊服務的營運成本。過去的研究顯示，越高的摘要壓縮比（摘要結果越短），摘要的成效越低，亦即困難度越高。手機新聞簡訊自動摘要，正好屬於高壓縮比、長度有限的極短摘要。本方法的特點在於衡量新聞句子的重要性，並找出句子與標題的相似點，結合成摘要候選句，最後依照其長度比例與相似度排序，供使用者選用。透過40 篇即時新聞的驗證，顯示從系統提示的第一候選句，即可獲得最佳摘要的比例達62.5%到65%。若從系統提示的所有候選句中挑選，可得最佳摘要的比例達75%到80%。相對的，系統無法做出好摘要的比例，則約20%到25%。關鍵詞：手機、新聞簡訊、自動摘要、中文、簡訊摘要Using the Web as Corpus for Un-supervised Learning in Question AnsweringYi-Chia Wang, Jian-Cheng Wu, Tyne Liang1 and Jason S. ChangAbstractIn this paper we propose a method for unsupervised learning of relation between terms in questions and answer passages by using the Web as corpus. The method involves automatic acquisition of relevant answer passages from the Web for a set of questions and answers, as well as alignment of wh -phrases and keywords in questions with phrases in the answer passages. At run time, wh-phrases and keywords are transformed to a sequence of expanded query terms in order to bias the underlying search engine to give higher rank to relevant passages. Evaluation on a set of questions shows that our prototype improves the performance of a question answering system by increasing the precision rate of top ranking passages returned by the search engine.應用語料庫和語意相依法則於中文語音文件之摘要Spoken Document Summarization Using Topic-Related Corpus and Semantic Dependency Grammar黃建霖、謝嘉欣、吳宗憲摘要自動語音文件摘要技術，可應用於資訊的檢索、語意壓縮及資料記錄等方面。目前自動語音摘要存在幾個問題，首先是語音辨識準確率的提升，以及如何對語音內容萃取重要資訊、生成在句法及語意上合理的摘要結果。本論文提出應用主題相關語料庫和語意相依法則於中文語音文件之摘要。首先，語音文件透過大詞彙連續語音辨識的方法，將語音辨識成文字，並獲得摘要單元斷點、音節以及詞等資訊。語音摘要部份，就語音本質從五個分數去分析，分別為：語音辨識信賴分數、詞重要性分數、語言分數、句法結構分數及語意相依法則分數，而後利用動態規劃搜尋演算法(dynamic programming algorithm, DP)獲得初步摘要結果。最後，為了使摘要語音串接輸出能具平滑特性，我們將摘要語音的有效語音段取出，計算語音頻譜特徵，考慮串聯單元彼此間的流暢度，挑選語音文件中重複的單元以串接生成摘要語音。由實驗結果得知，本研究所提出之自動語音摘要架構與人工摘要結果相比，能有效地萃取重要資訊，串接合成流暢的摘要語音。具相關資訊回饋能力之貝氏混合式機率檢索模型Using Relevan