Cross-Lingual Neural Network Speech Synthesis Based on Multiple Embeddings

The paper presents a novel architecture and method for speech synthesis in multiple languages, in voices of multiple speakers and in multiple speaking styles, even in cases when speech from a particular speaker in the target language was not present in the training data. The method is based on the application of neural network embedding to combinations of speaker and style IDs, but also to phones in particular phonetic contexts, without any prior linguistic knowledge on their phonetic properties. This enables the network not only to efficiently capture similarities and differences between speakers and speaking styles, but to establish appropriate relationships between phones belonging to different languages, and ultimately to produce synthetic speech in the voice of a certain speaker in a language that he/she has never spoken. The validity of the proposed approach has been confirmed through experiments with models trained on speech corpora of American English and Mexican Spanish. It has also been shown that the proposed approach supports the use of neural vocoders, i.e. that they are able to produce synthesized speech of good quality even in languages that they were not trained on

Dubbing Wordplay in Children’s Programmes from English into Thai

This doctoral research aims to investigate the most prevalent translation techniques adopted by Thai dubbing translators when transferring English-language idioms found in animated films into a lesser-known language such as Thai. To achieve this purpose, the methodological approach combines a quantitative phase, which has the benefit of revealing certain tendencies, with a qualitative phase that investigates the data in greater depth. Wordplay instances can be grouped into two main categories according to their presentation nature: media-based and rhetoric-based. In the case of the media-based category, the types of wordplay instances uncovered in the analysis are audio-verbal, audio-visual-verbal and visual-verbal, while, based in the rhetoric-based category, they are homonymy, homophony, paraphony, hahaphony and allusion types. In an attempt to render ST puns into the TT, the following seven dubbing techniques have been activated by Thai translators: loan, literal translation, explicitation, substitution, recreation, combination and non-translation. Close examination of the data reveals that, despite the translators’ best effort to transfer the semantic ambiguity and humorous effect embedded in the English wordplay into the Thai dialogue, PUN>NON-PUN is the translation outcome with the highest occurrence. This results in the inevitable loss of semantic ambiguity and humour in the TT wordplay, as well as other pedagogical objectives intended by the film’s producers such as a language learning facilitator for young viewers

The Arabic (Re)dubbing of Wordplay in Disney Animated Films

Although audiovisual translation (AVT) has received considerable attention in recent years, evidence suggests that there is a paucity of empirical research carried out on the dubbing of wordplay in the Arabophone countries. This piece of research sets to identify, describe and assess the most common translation techniques adopted by translators when dubbing English-language animated films into Arabic. The focus is on the special case of dubbing Disney animated films into Egyptian Arabic (EA) and their subsequent redubbing into Modern Standard Arabic (MSA), during the 1975-2015 period. The ultimate goal is to ascertain the similarities as well as the differences that set the two versions apart, particularly when it comes to the transfer of wordplay. To reach this objective, the methodological approach adopted for this study is a corpus of instances of wordplay that combines a quantitative phase, which has the advantage of identifying correlations between the types of wordplay and particular translation techniques and results and is then followed by a qualitative analysis that further probes the results and determines the different factors that contribute to the way wordplay is translated. The analysis reveals that, in their attempt to render this type of punning humour, in both Arabic dubbed versions, Arabic translators resort to a variety of translation techniques, namely, loan, direct translation, explication, paraphrase, substitution and omission. The examination of the data shows that achieving a humorous effect in the target dialogue is the top priority and driving factor influencing most of the strategies activated in the process of dubbing wordplay into EA. Dissimilarly, there is a noticeable lower amount of puns crossing over from the original films to the MSA dubbed versions, highlighting the fact that the approach generally taken by the dubbing teams seems to give priority to the denotative, informative dimension rather than the socio-pragmatic one. By shedding light on the intricacies of dubbing, it is hoped that this study would contribute to the advancement of knowledge in the translation of wordplay in the Arabophone countries and, more specifically, in the field of dubbing children’s programmes

THE TRENDS OF SKRIPSI AND THESIS TOPICS ON TRANSLATION AT UNIVERSITIES IN INDONESIA

Ada banyak bidang penelitian penerjemahan yang dapat dilakukan mahasiswa sebagai topik skripsi dan tesis. Sejalan dengan meningkatnya jumlah penelitian penerjemahan oleh mahasiswa, tren atau kecendrungan topik muncul di antara skripsi dan tesis mahasiswa. Penelitian ini bertujuan untuk mendapatkan data mengenai tren topik dalam skripsi dan tesis mahasiswa di Indonesia. Sumber data dalam penelitian ini adalah skripsi dan tesis bidang penerjemahan di Jurusan Bahasa Inggris tingkat S1 dan S2 yang diselidiki topik berdasarkan judul skripsi dan tesis tersebut. Ada 280 skripsi yang dikumpulkan dari sejumlah universitas di Jawa dan Bali; dan 83 tesis yang diambil dari beberapa universitas yang tersebar di Jawa, Bali, dan Sumatra. Penelitian ini menggunakan metode deskriptifanalitikal interpretif dengan teknik pengumpulan dan analisis data menggunkan kajian dokumen. Analisa dalam penelitian ini adalah pengklasifikasian topik-topik ke dalam 12 wilayah penelitian penerjemahan yang dijelaskan oleh Willliam dan Chestermann (2002). Hasil penelitian menunjukkan dari ke-12 wilayah tersebut, ada satu wilayah dalam skripsi tentang penerjemahan yang tidak diselidiki oleh mahasiswa, yaitu Translation History. Sedangkan pada tesis mahasiswa. Ada lima wilayah yang tidak diteliti mahasiswa: Translation and Technology, Translation History, Interpreting, Translator Training, dan Translation Profession.Tren topik penelitian penerjemahan pada skripsi dan tesis adalah Text Anlaysis and Translation . Pada skripsi, wilayah Text Anlaysis and Translation memiliki persentase terbesar, 56.42% (158 skripsi) dengan strategi dalam menerjemahan novel merupakan topik yang paling dominan dipilih mahasiswa. Pada tesis, wilayah Text Analysis and Translation memiliki persentase 77,11% (64 tesis). Topik yang dominan diselidiki adalah strategi penerjemahan novel dan penerjemahan beranotasi yang kebanyakan subjek yang diteliti adalah novel. Dapat disimpulkan bahwa masih ada wilayah penelitian penerjemahan yang jarang ataupun belum diangkat sebagai topik dalam skripsi dan tesis. Text Analysis and Translation menjadi tren bisa jadi berkaitan dengan kurikulum dan keterbatasan referensi mengenai penerjemahan. Dari beberapa contoh kurikulum yang diambil, mata kuliah lingkup penerjemahan di beberapa universitas jumlahnya masih belum banyak. Pada program S2, walau ada jurusan dengan peminatan penerjemahan, mata kuliah yang diajarkan berhubungan erat dengan mata kuliah linguistik. Jadi wilayah yang banyak diteliti adalah Text Analysis and Translation. There are couples of areas in translation research that can be conducted by students as their skripsi and theses. In conjunction with the increasing number of students’ research on translation, topic trends appear amongst the students’ skripsi and theses. This study aims to investigate the topic trends on translation research in students’ skripsi and theses at universities in Indonesia. The sources of the data were skripsi and theses on translation at English Department in both Bachelor Degree and Master Degree Program whose topics were taken from the title of those skripsi and theses. There are 280 skripsi collected at several universities in Java and Bali; and 83 theses were taken from some universities spread in Java, Bali, and Sumatra. Descriptive analytical interpretive method was applied to conduct the research. The data collection technique and analysis was done by using document study. The analysis was the classification of the topics into the 12 areas of translation research explained by William and Chestermann (2002). The result shows that from those 12 areas, there is one area in skripsi which was not investigated by student, that is Translation History and in thesis five of 12 areas were not examined, those are: Translation and Technology, Translation History, Interpreting, Translator Training, and Translation Profession. It is also found that the trend is Text Analysis and Translation area either in skripsi or thesis. In skripsi it made up 56.42% or 158 research topics which investigated strategies used in translating novel. In theses, Text Analysis and Translation has 64 research topics or 77.11%. The topics are prominently about strategies used in novel translation and annotated translation which the subjects used are novel as well. It can be concluded that some other areas on translation research that have not been investigated yet as the topics either in students’ skripsi or theses. Text Analysis and Translation becomes the dominant trend in students research might deal with the curriculum designed for translation subject and the limitation of references on translation. From the sample of curriculum taken, the subject of translation in some English Department is just a little in number. In the Master Degree program, although there is a proclivity on translation, the subjects on translation are dominantly dealt with the linguistics subjects. So the area that can be explored greatly is Text Analysis and Translation

The Whitworthian 2007-2008

The Whitworthian student newspaper, September 2007-April 2008.https://digitalcommons.whitworth.edu/whitworthian/1092/thumbnail.jp

A Mandarin Text-to-speech System Using A Large Number Of Words As Synthesis Units

近年來，文轉音(Text-to-Speech)系統漸漸以Corpus-based的架構來實作，並以波形拼接來做為合成方法。該方法的優點在於可以得到不錯的語音品質，相較於傳統以音節為合成單元的架構，更容易被聽者接受。這種架構的特徵在於：（一）會錄製大量語料（二）盡可能不做訊號處理（三）選擇適當的合成單元。軟體界的巨人–微軟，所推出的「木蘭」雙語(中文以及英語)TTS系統，便是使用Corpus -based的方式所組成的。錄音的語料為錄製句子(sentence)。在連續音語料上採用一個階層式的韻律模型。最後再利用Decision Tree的方法來找尋適當的非固定長度合成單元來進行拼接，過程中，完全不做訊號處理。我們有鑒於錄製句子，可能無法錄到一些罕見詞，以及考慮到詞跟詞之間的連音現象(Co-articulation)較微弱。所以嘗試使用大量詞彙(word-based)當成我們的合成單元，並使用rule- based的方法來挑音拼接，會做小部份的訊號處理：Fading-in和Fading-out。最後，我們總共錄製了約12224個二字詞、2690個三字詞。停頓對於聽者而言，是一個幫助理解句子涵義的非常重要的韻律特徵，我們採用CART(Classification And Regression Tree)預測韻律邊界，當成停頓的依據。在本論文中，最終會完成一套中文文轉音系統，並且進行了自然度、可辨度和偏好測試來當成實驗結果。In recent years, many TTS(Text to Speech) systems were implemented in a corpus-based structure. Synthesis units are directly connected in synthesizing, This method can get good speech quality. Compared with traditional TTS using syllables as synthesis units, it is more acceptable to the listeners. This type of system have the following features: (1) Recording a large speech corpus. (2) Signal processing is not used. (3)Select proper synthesis units. A powerful company - Microsoft, has developed a corpus-based bilingual ( Mandarin / English ) system - Mulan. The corpus is constructed by recording sentences. In their corpus, a hierarchical prosodic structure is used. In the module of selecting non-uniform synthesis units, decision tree is used. There is no signal processing in the procedure. However, rare words may not appear in the recorded sentences. Another reason is that there is weak co-articulation between word and word. So, we decide to use a word set (word-based) as synthesis units, and use rule-based methods to select synthesis units. There is little signal processing - only Fading-in and Fading-out. Totally, we have recorded about 12224 two-character words and 2690 three-character words. Break in speaking is very important in understanding a sentence. We employ CART (Classification And Regression Tree) to predict boundary types. The result is used to make corresponding break. In this paper, we implemented a Mandarin TTS system. We preformed naturalness testing, preference testing and intelligibility testing in our evaluation.摘要 I ABSTRACT III 目錄 IV 表索引 VII 圖索引 VIII 第一章 緒論 1 1.1文轉音系統的架構 1 1.2以詞為基礎的系統架構 7 1.3論文架構 11 第二章 文句分析 13 2.1 斷詞單元及構詞單元 14 2.1.1斷詞方法 15 2.1.2 構詞規則 19 2.1.3 斷詞單元實驗數據 20 2.2標記詞類單元 22 2.2.1 考慮詞的bigram模型 23 2.2.2標記詞類的實驗數據 25 2.3字轉音及連音變調 25 2.3.1字轉音 25 2.3.2連音變調規則 26 2.3.3連音變調的問題 29 第三章 韻律預估 31 3.1 CART方法介紹 32 3.2預測韻律邊界 38 3.2.1 預測使用的特徵 39 3.2.2預測實驗與結果 41 3.3預估音量與音長 43 3.3.1 預估方法概要 44 3.3.2 預估數據的轉換 47 第四章 單元選取與韻律調整 49 4.1音檔錄製與切音工作 49 4.2選音策略 52 4.2.1 詞中挑選單音的方法 53 4.2.2 選音範例 59 4.2.3 以音高為依據來從詞中選擇單音 61 4.3韻律調整(音長、音量、停頓) 62 4.3.1音長 62 4.3.2音量 64 4.3.3停頓 64 4.3.4連音規則 66 4.4合成單元的平滑化 67 第五章 測試實驗與結果 69 5.1 自然度測試 69 5.2偏好測試 70 5.3可辨度測試 72 第六章 未來的工作與討論 74 參考文獻 77 附錄一 79 附錄二 91 附錄三 92 附錄四 94 附錄五 9